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Cluster :  Posters

Session Information  : Tuesday Nov 03, 12:30 - 14:30

Title:  Tuesday Poster Session
Chair: Min Wang,Drexel University, 3141 Chestnut Street, Philadelphia PA, United States of America, mw638@drexel.edu
Co-Chair: Wenjing Shen,Drexel University, Philadelphia PA, United States of America, ws84@drexel.edu
Allen Holder,Rose-Hulman Mathematics, Terre Haute IN, United States of America, holder@rose-hulman.edu

Abstract Details

Title: Surgery Scheduling with Recovery Resources
 Presenting Author: Maya Bam,University of Michigan, Industrial and Operations Engineering, 1205 Beal Ave., Ann Arbor MI 48109, United States of America, mbam@umich.edu
 Co-Author: Mark Cowen,St. Joseph Mercy Health System, Quality Institute, 5333 McAuley Dr., Ypsilanti MI 48197, United States of America, mark.cowen@stjoeshealth.org
 Brian Denton,Univerisity of Michigan, Industrial and Operations Engineering, 1205 Beal Ave., Ann Arbor MI 48109, United States of America, btdenton@umich.edu
 Mark Van Oyen,University of Michigan, Industrial and Operations Engineering, 1205 Beal Ave., Ann Arbor MI 48109, United States of America, vanoyen@umich.edu
 
Abstract: Surgery scheduling is complicated by the post-anesthesia care unit, the typical recovery resource. Based on collaboration with a hospital, we present a novel, fast 2-phase heuristic that considers both surgery and recovery resources. We show that each phase of the heuristic has a tight provable worst-case performance bound. Moreover, the heuristic performs well compared to optimization based methods when evaluated under uncertainty using a discrete event simulation model.
  
Title: Inventory Control with Unknown Demand and Nonperishable Product
 Presenting Author: Tingting Zhou,Rutgers University, 1 Washington Park, Newark NJ 07102, United States of America, tingzhou@rutgers.edu
 Co-Author: Michael Katehakis,Rutgers University, 1 Washington Park, Newark NJ 07102, United States of America, mnk@rci.rutgers.edu
 Jian Yang,Rutgers University, 1 Washington Park, Newark NJ 07102, United States of America, jyang@business.rutgers.edu
 
Abstract: We study an inventory control problem with unknown discrete demand distribution, focusing on the analysis of an adaptive algorithm based on empirical distributions and the newsvendor formula. When items are nonperishable, the algorithm can achieve a near square-root-of-T bound on its regret over the ideal case where demand distribution were known.
  
Title: Optimizing Information System Security Investments with Risk: Insights for Resource Allocation
 Presenting Author: Yueran Zhuo,PhD Candidate, University of Massachusetts Amherst, Isenberg School of Management, Amherst MA 01003, United States of America, yzhuo@som.umass.edu
 Co-Author: Senay Solak,University of Massachusetts Amherst, Isenberg School of Management, Amherst MA 01003, United States of America, solak@isenberg.umass.edu
 
Abstract: Information security has become an integral component of a firm's business success, and thus investing on information security countermeasures is an important decision problem for many businesses. We use a portfolio approach to study the optimal investment decisions of a firm, where the uncertainty of information security environment is captured through a stochastic programming framework. Results cast managerial insights for information security investment planning by a firm.
  
Title: Adaptive Decision-Making of Breast Cancer Mammography Screening: A Heuristic-Based Regression Model
 Presenting Author: Fan Wang,University of Arkansas,, Fayettevlle AR, United States of America, fxw005@uark.edu
 Co-Author: Shengfan Zhang,University of Arkansas,, Fayetteville AR, United States of America, shengfan@uark.edu
 
Abstract: The American Cancer Society currently recommends all U.S. women undergo routine mammography screenings beginning at age 40. However, due to the potential harms associated with screening mammography, such as overdiagnosis and unnecessary work-ups, the best strategy to design an appropriate breast cancer mammography screening schedule remains controversial. This study presents a mammography screening decision model that aims to identify an adaptive screening strategy while considering disadvantages of mammography. We present a two-stage decision framework: (1) age- specific breast cancer risk estimation, and (2) annual mammography screening decision-making based on the estimated risk. The results suggest that the optimal combinations of independent variables used in risk estimation are not the same across age groups. Our optimal decisions outperform the existing mammography screening guidelines in terms of the average loss of life expectancy. While most earlier studies improved the breast cancer screening decisions by offering lifetime screening schedules, our proposed model provides an adaptive screening decision aid by age. Since whether a woman should receive a mammogram is determined based on her breast cancer risk at her current age, our “on-line” screening policy is adaptive to a woman’s latest health status, which causes less bias in reflecting the individual risk of every woman.
  
Title: Optimization of Netting Scheme in Large-scale Payment Network
 Presenting Author: Shuzhen Chen,University of Science & Technology of China, NO. 98, Jinzhai Road, Hefei, China, csz@mail.ustc.edu.cn
 
Abstract: As netting becomes combined with real-time settlement, an efficient netting method is required to deal with the large-scale payment network. Network optimization may not be optimal due to repeated searching of shortest path. A new method is proposed to optimize the netting process by assembling payments in two specific routes. It can minimize the amount of total payments for the whole network and ensure unchanged net payment for each bank. Moreover, it has polynomial time-complexity.
  
Title: Wasserstein Metric and the Distributionally Robust TSP
 Presenting Author: Mehdi Behroozi,University of Minnesota, Minneapolis MN, United States of America, behro040@umn.edu
 Co-Author: John Gunnar Carlsson,University of Southern Califonia, United States of America, jcarlsso@usc.edu
 
Abstract: Recent research on the robust and stochastic travelling salesman problem and the vehicle routing problem has seen many di?erent approaches for describing the region of uncertainty, such as taking convex combinations of observed demand vectors or imposing constraints on the moments of the spatial demand distribution. One approach that has been used outside the transportation sector is the use of statistical metrics that describe a distance function between two probability distributions. In this paper, we consider a distributionally robust version of the Euclidean travelling salesman problem in which we compute the worst-case spatial distribution of demand against all distributions whose earth mover’s distance to an observed demand distribution is bounded from above. This constraint allows us to circumvent common overestimation that arises when other procedures are used, such as fixing the center of mass and the covariance matrix of the distribution.
  
Title: Intersection of a Tree Network for the Single Refueling Station Location Problem
 Presenting Author: Sang Jin Kweon,PhD Student, The Pennsylvania State University, 310 Leonhard Building, State College PA 16802, United States of America, svk5333@psu.edu
 
Abstract: An intersection is the vertex whose degree is greater than two in the network. In this talk, we consider intersections and develops the methodology that determines the continuous interval of the potential locations for a single alternative-fuel refueling station on a tree network, with an objective of maximizing the amount of traffic flows in round trips per time unit captured by the station.
  
Title: Intelligent Tutoring Systems: Future Paradigm of Educational Environments
 Presenting Author: Alireza Farasat,University at Buffalo (SUNY), 4433 Chestnut Ridge Rd Apt 7, Amherst NY 14228, United States of America, afarasat@buffalo.edu
 Co-Author: Alexander Nikolaev,Assistant Professor, University at Buffalo (SUNY), 312 Bell Hall, Amherst NY 14260, United States of America, anikolae@buffalo.edu
 
Abstract: Educational systems have witnessed a substantial transition from traditional educational methods mainly using text books, lectures, etc. to newly developed systems which are artificial intelligent-based systems and personally tailored to the learners. We have developed a web-based tool, Crowdlearning which concentrates on creating an intelligent system that learns to interact with students and motivates them to more actively participate in the learning process by proposing their own problems.
  
Title: Optimized Scheduling of Sequential Resource Allocation Systems
 Presenting Author: Ran Li,Ph.d. Student, Georgia Institute of Technology, 755 Ferst Drive NW, Atlanta GA 30332, United States of America, rli63@gatech.edu
 Co-Author: Spyros Reveliotis,Professor, Georgia Institute of Technology, 765 Ferst Dr NW, Atlanta GA 30332, United States of America, spyros@isye.gatech.edu
 
Abstract: We consider the scheduling problem of allocating finite reusable resources to concurrent sequential processes. This problem also involves the logical issue of deadlock avoidance. Our approach is based on the formal model of the generalized stochastic Petri-net. Special emphasis is placed on the representational and computational complexity of the proposed methods, which are controlled through (i) a pertinent (re-)definition of the target policy spaces, and (ii) simulation optimization.
  
Title: Operation Research for Data Mining: An Application to Medical Diagnosis
 Presenting Author: Shahab Derhami,Auburn University, 3301 Shelby Center, Auburn GA 36849, United States of America, sderhami@auburn.edu
 
Abstract: Fuzzy rule based classification systems (FRBCSs) have been successfully employed as a data mining technique where the goal is to discover the hidden knowledge in a data set and develop an accurate classification model. Despite various heuristic approaches that have been proposed to learn fuzzy rules for these systems, no exact optimization approach has been developed for this problem. We propose integer programming models to learn fuzzy rules for a FRBCS used for medical diagnosis purpose.
  
Title: Forecasting Surges in the Hospital Emergency Department (ED)
 Presenting Author: Alexander Gutfraind,Chief Healthcare Data Scientist, Uptake Technologies, 600 W. Chicago Avenue, Chicago IL 60654, United States of America, sasha.gutfraind@uptake.com
 Co-Author: Nelson Bowers,Senior Manager, Uptake Technologies, 600 W. Chicago Avenue, Chicago IL 60654, United States of America, nelson.bowers@uptake.com
 Jim Herzog,Data Science Manager, Uptake Technologies, 600 W. Chicago Avenue, Chicago IL 60654, United States of America, jim.herzog@uptake.com
 Madeline Jannotta,Ux Scientist, Uptake Technologies, 600 W. Chicago Avenue, Chicago IL 60654, United States of America, madeline.jannotta@uptake.com
 Ilan Kreimont,Product Manager, Uptake Technologies, 600 W. Chicago Avenue, Chicago IL 60654, United States of America, ilan.kreimont@uptake.com
 Adam Mcelhinney,Director Of Data Science, Uptake Technologies, 600 W. Chicago Avenue, Chicago IL 60654, United States of America, adam.mcelhinney@uptake.com
 
Abstract: A major hospital system in the Chicago metro area experiences large unexpected surges in its Emergency Department (ED). Using five years of ED admissions we predict ED surges and improve scheduling of staff. Data indicates the time of arrival, rooming and discharge and acuity. Total arrivals per day cannot be predicted accurately with epidemiological climatological, calendar variables but the state of the ED could be predicted 1-4 hours in advance with high accuracy using VAR methods.
  
Title: A New Measure for Testing Independence
 Presenting Author: Qingcong Yuan,Graduate Student, University of Kentucky, 300 Alumni Drive Apt 166, Lexington KY 40503, United States of America, qingcong.yuan@uky.edu
 Co-Author: Xiangrong Yin,Professor Of Statistics, University of Kentucky, 319 MDS, 725 Rose St., Lexington KY 40536, United States of America, yinxiangrong@uky.edu
 
Abstract: We introduce a new measure for testing independence between two random vectors. Our measure differs from that of distance covariance, by using expected conditional difference of characteristic functions. We propose one empirical version by slicing on one of the random vectors. This empirical measure is based on certain Euclidean distance. Its properties, asymptotics and applications in testing independence are discussed. Implementation and Monte Carlo results are also presented.
  
Title: Graph Based Non-isometric Curve to Surface Matching for Local Calibration
 Presenting Author: Babak Farmanesh,Ph.d. Student, Oklahoma State University, 322 Engineering North, Stillwater OK 74078-5016, United States of America, babak.farmanesh@okstate.edu
 Co-Author: Balabhaskar Balasundaram,Associate Professor, Oklahoma State University, 322 Engineering North, Stillwater 74078-501, United States of America, Baski@okstate.edu
 Arash Pourhabib,Assistant Professor, Oklahoma State University, 322 Engineering North, Stillwater OK 74078-5016, United States of America, arash.pourhabib@okstate.edu
 
Abstract: Calibration refers to the process of adjusting parameters of a computer simulation so that the simulation responses match the corresponding physical responses. Calibration can be interpreted as a curve to surface matching problem. We propose a graph-theoretic non-isometric matching approach to solve this problem using the graph shortest path algorithm in one-dimensional spaces. For higher dimensional spaces, we introduce the generalized shortest path concept to solve the matching problem.
  
Title: Location and Coverage Models for Preventing Attacks to Interurban Transportation Networks
 Presenting Author: Ramón Auad,Associate Professor, Universidad Católica del Norte, Of. 318, BLDG Y1, 0610 Angamos Avenue, Antofagasta 1240000, Chile, rauad@ucn.cl
 Co-Author: Rajan Batta,Suny Distinguished Professor, Department Of Industrial & Systems Engineering, State University of New York at Buffalo, 410 Bell Hall, University at Buffalo, (State University of New York), Buffalo NY 14260, United States of America, batta@buffalo.edu
 
Abstract: We develop a binary integer programming model to solve this problem, whose objective is to maximize the expected vehicle coverage across the network over a time horizon, using decomposition heuristics. To introduce a measure of equity, we propose two sets of time constraints, considering total vehicle coverage, inequity and network coverage. We explore scalability of the model for excessively large instances. All of this features are applied to a case study in Northern Israel.
  
Title: An Information-based Framework for Incorporating Travel Time Uncertainty in Transportation Modeling
 Presenting Author: Jiangbo Yu,University of California, Irvine, 4101 Palo Verde Rd, Irvine CA 92617, United States of America, jiangby@uci.edu
 Co-Author: Jay Jayakrishnan,Professor, University of California, Irvine, 4101 Palo Verde Rd, Irvine CA 92697-3600, United States of America, rjayakri@uci.edu
 
Abstract: This paper proposes a modeling framework aimed at systematically incorporating perceived uncertainty into decision making. The model uses theoretically sound concepts from information theory, communication, and cognitive science. Potential applications and implications are identified and demonstrated with examples.
  
Title: Database of Identified Poly and Mono ADP-ribosylated Proteins
 Presenting Author: Charul Agrawal,Undergraduate Student, Indian Institute of Technology (IIT) Delhi, Room No ED-16, Himadri Hostel, Hauz Khas, New Delhi 110016, India, agrawalcharul09@gmail.com
 
Abstract: Poly(ADP-ribose) polymerase (PARP) is a family of enzymes with 17 known members regulating post translational modification of proteins by attaching a single ADP ribose unit (MARylation) or a chain of ADP ribose (PARylation).In this study we have attempted to identify all proteins known to be modified by PARPs and the methods as well as drugs used in such studies. Our study aims to create the first ever tool for characterizing these modifications.
  
Title: Configuring Ecommerce Driven Supply Chains in the FMCG Sector
 Presenting Author: Stanley Lim,Phd Candidate, Cambridge University, Department of Engineering, 17 Charles Babbage Road, Cambridge, United Kingdom, wtsfl2@cam.ac.uk
 
Abstract: Omnichannel has become the engine of growth in retailing. However, it remains unclear as to how distribution networks should be configured. This research will shed light through a framework development, and by drawing theories from supply chain configuration, resource based view, and transaction cost economics. Case study approach is adopted to identify the critical factors driving operational choices and seeks to elaborate the relationships between configuration, capability and performance.
  
Title: Benchmarking Construction and Improvement Heuristics for Classification using Markov Blankets
 Presenting Author: Daniel Gartner,Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh PA 15213, United States of America, dgartner@andrew.cmu.edu
 Co-Author: Rema Padman,Professor Of Management Science & Healthcare Informatics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh PA 15213, United States of America, rpadman@cmu.edu
 
Abstract: This study examines construction heuristics in connection with a tabu search-based improvement heuristic for classification in high dimensional data sets. Using the UCI machine learning data repository containing benchmark instances in e.g. health care, we evaluate computation times and information about the evolution of the Markov blanket graphical models in each phase of the heuristics. We compare the performance of the approaches using evaluation measures such as classification accuracy.
  
Title: A Sim-heuristic Algorithm for Robust Vehicle Routing Problems with Stochastic Demand
 Presenting Author: Abdulwahab Almutairi,Technology, 9 Horizon Building, Portsmouth PO4 8EW, United Kingdom, abdulwahab.m.almutairi@gmail.com
 
Abstract: We consider the VRPSD in which customers’ demands are stochastic. We propose to model and solve the VRPSD by developing a robust optimisation model with a sim-heuristic solution method to minimise the cost while satisfying all demands. The method combines MCS with CWS in order to efficiently solve the VRPSD combinatorial optimisation problem. The results is generating very good quality solutions compared to those in the literature.
  
Title: Rocket Stage Optimization in Kerbal Space Program
 Presenting Author: Nathan Arrowsmith,Rochester Institute of Technology, 2800 Butternut Lane, Canandaigua NY 14424, United States of America, nea4305@rit.edu
 
Abstract: Kerbal Space Program is a space exploration simulation game. Players design, launch, and fly multi-stage rockets using a variety parts. The performance of these vehicles is governed by a realistic physics engine. A model was developed which minimizes the total mass of each rocket stage by choosing motor and fuel tank combinations which accurately satisfy the Tsiolkovsky Rocket Equation. By iteratively solving this problem, the lowest mass or least expensive multi-stage rocket can be determined.
  
Title: Investigation of the Effect of Location, Built Environment and Urban Forms on Customer Satisfaction
 Presenting Author: Homa Atefyekta,Sharif University of Technology, No.14, 5th St., South Piruzan St, Tehran 1466643479, Iran, homa.atefyekta@gmail.com
 Co-Author: Hamed Ahangari,Resercher At University Of Coneccticut, Civil and environment and engineering department, 142 vernon ave. apt 83, vernon CO 06066, United States of America, h.ahangari@gmail.com
 Hoda Atef Yekta,Phd Candidate, University of Connecticut, Storrs CT 06268, United States of America, h.atefyekta@gmail.com
 
Abstract: In this study we examine the effect of location factors, urban forms, transportation accessibilities, and built environment on the customer satisfaction and business success in restaurant market. We investigated these relationships in two different geographical areas: the US and Iran by using Yelp and Fidilio data respectively. The results of this study could be handful for urban policy makers to improve the urban livability and business entrepreneurs to enhance the odd of their success.
  
Title: What do Equity Hedge Funds Really do? Evidence in the QE Period
 Presenting Author: Geum Il Bae,KAIST, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea, Republic of, gi_bae@kaist.ac.kr
 Co-Author: Woo Chang Kim,Dr., Korea Advanced Institution of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, Korea, Republic of, wkim@kaist.ac.kr
 Sun Young Park,Dr., KAIST, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea, Republic of, sunyoung.park@kaist.ac.kr
 
Abstract: We examine why the hedge fund industry has experienced a slump during the “Quantitative Easing (QE)” period. We analyze the risk-adjusted performances of equity hedge funds in the pre-crisis, crisis, and QE periods. We show that the disappeared alpha is the main reason for the inferior performance of hedge fund industry these days, and reduction in exposure to systematic risks further explains the underperformance of hedge funds in the QE period.
  
Title: NEOS Server: State-of-the-art Solvers for Numerical Optimization
 Presenting Author: Rosemary T. Berger,University of Wisconsin - Madison, 330 N. Orchard St., Madison WI 53715, United States of America, rosemary.t.berger@gmail.com
 Co-Author: Michael Ferris,University of Wisconsin - Madison, 1210 West Dayton Street, Madison WI 53706, United States of America, ferris@cs.wisc.edu
 Jeff Linderoth,University of Wisconsin - Madison, 1513 University Avenue, Madison WI 53706, United States of America, linderoth@wisc.edu
 
Abstract: The NEOS Server is a free internet-based service for solving numerical optimization problems. Hosted by WID at the University of Wisconsin in Madison, the NEOS Server provides access to more than 60 state-of-the-art solvers in more than a dozen optimization categories. Solvers run on distributed high-performance machines enabled by the HTCondor software. We describe recent enhancements to the NEOS Server and highlight new interactive optimization cases studies available on the NEOS Guide.
  
Title: ***NO SHOW***Provable Submodular Function Minimization via Wolfe's Algorithm
 Presenting Author: Deeparnab Chakrabarty,Dr, Microsoft, 9 Lavelle Road, Bangalore, India, deeparnab@gmail.com
 
Abstract: Submodular function minimization (SFM) is an essential paradigm which appears in many areas such as large scale learning and computer vision. The Fujishige-Wolfe Algorithm is agreed to be the fastest emprirical SFM algorithm. Despite its good practical performance, very little is known about Wolfe’s minimum norm algorithm theoretically. In this paper we give the first polynomial time convergence analysis of Fujishige-Wolfe’s algorithm.
  
Title: ***NO SHOW***Stochastic PDE-constrained Optimization of Vibrations of a Plate Under a Piecewise-linear Current
 Presenting Author: Dmitry Chernikov,The University of Iowa, 1010 W Benton St #208F, Iowa City IA 52246, United States of America, scher.de@gmail.com
 Co-Author: Pavlo Krokhmal,The University of Iowa, University of Iowa 2136 Seamans Center, Iowa City IA 52242, United States of America, krokhmal@engineering.uiowa.edu
 Olesya Zhupanska,University of Iowa, 2416A Seamans Center, Iowa City IA 52242, United States of America, ozhupans@engineering.uiowa.edu
 
Abstract: In this work a two-stage stochastic PDE-constrained optimization framework is applied to the problem of vibration control of a thin composite plate in the presence of electromagnetic field. The electric current is assumed to be of a piecewise-linear form. We compute the gradient of the objective function using adjoint numerical differentiation method. The value of the objective function is calculated by solving the governing PDEs, and a black-box approach is used for the minimization problem.
  
Title: Assessing Kernel-based Anomaly Detection Algorithms
 Presenting Author: Hyun-chang Cho,Seoul National University, Banpo-gu, Seocho-dong, Seoul, Korea, Republic of, hccho@dm.snu.ac.kr
 Co-Author: Sungzoon Cho,Professor, Seoul National University, Bangbae1-dong, Seocho-gu, Seoul, Korea, Republic of, zoon@snu.ac.kr
 
Abstract: Anomaly detection is the process of finding items which do not comply with the normal pattern of the data set. Although kernel-based approaches seem to be promising for detecting anomalies, they have not been compared in a systematic way. In this study, we generated numerous well-calibrated benchmark data set and use them to evaluate the performance of various kernel-based anomaly detection algorithms. The effect of kernel parameters will also be empirically investigated.
  
Title: Simulation Analysis of Chaotic Storage Policies in Amazon Class Fulfillment Centers
 Presenting Author: Sanchoy Das,New Jersey Institute of Technology, University Heights, Newark NJ 07102, United States of America, das@njit.edu
 Co-Author: Sevilay Onal,Research Assistant, New Jersey Institute Of Technology, University Heights, Newark NJ 07102, United States of America, so59@njit.edu
 
Abstract: We evaluate storage policies in Amazon Class Fulfillment (ACF) Centers that primarily serve internet retail. In classical warehouses a SKU is stored in few fixed locations, no comingling, in bulk volumes and long interval supply. In a chaotic policy each SKU is stored in any location, comingled, closer to retail volumes and frequent supply. In an ACF fulfillment time is the primary objective. We use a simulator model to analyze and present the relative performance for given levels of workforce.
  
Title: Spatial-temporal Coverage Evaluation Methodology for Multi-satellite Embedded Sensors
 Presenting Author: Maria Jose Pinto,Dra, Institute for Advanced Studies, Cel Av Jose Alberto A do Amarante, 1, Sao Jose dos Campos SP 12228001, Brazil, maju@ieav.cta.br
 Co-Author: Diogo Maciel Almeida,Instituto for Advanced Studies, Cel Av Jose Alberto A do Amarante, 1, Sao Jose dos Campos, Brazil, dio.msg@gmail.com
 Monica Maria De Marchi,Dra, Institute for Advanced Studies, Cel Av Jose Alberto A do Amarante,1, Sao Jose dos Campos SP 12228001, Brazil, monica@ieav.cta.br
 Osvaldo Catsumi Imamura,Institute for Advanced Studies, Cel Av Jose Alberto A do Amarante, 1, Sao Jose dos Campos, Brazil, catsumi@ieav.cta.br
 
Abstract: The intent of this research is to propose an optimized coverage model for satellite systems and support the decision-making process related to choosing the best satellites in a scenario of interest. The appropriate satellites are those whose sensors are able to visualize and identify targets. The decision model proposed trades off between temporal resolution and the coverage area extension, but also considers the cost to obtain the image and the resolution provided by the different sensors.
  
Title: Stochastic Optimization Methods for Nurse Staffing in Inpatient Settings
 Presenting Author: Parisa Eimanzadeh,Wichita State University, 1845 Fairmount Street, Wichita KS 67260, United States of America, pxeimanzadeh@wichita.edu
 Co-Author: Ehsan Salari,Wichita State University, 1845 N Fairmount,, Industrial and Manufacturing Engineering, wichita KS 67260-0035, United States of America, ehsan.salari@wichita.edu
 
Abstract: In this study, we use Queueing Theory and discrete-event simulation techniques to determine nurse-staffing strategies that minimize staffing costs and ensure timely delivery of nursing care to patients while accounting for the heterogeneity in patients' acuity and staff skill levels.
  
Title: A Systems Dynamics Model for Flight Test Knowledge Management
 Presenting Author: Roberto Follador,Mr, Institute for Advanced Studies - IEAv, Trevo Coronel Av Jose A. A.Amarante, 01, Putim, Sao Jose dos Campos SP 12228-001, Brazil, rcfollador@gmail.com
 
Abstract: The research investigated how Knowledge Management (KM), in a Brazilian Air Force (BAF) flight test environmen can be represented via a Systems Dynamics Model. A documental research regarding the flight test environment KM was done and a questionnaire was submitted to identify KM characteristics.
  
Title: A Supply Chain Network Equilibrium Model with Carbon Capacity and Social Responsibility
 Presenting Author: Xiaoling Fu,School of Economics and Management, Southeast University, Si Pai Lou 2#, Nanjing 210096, China, fufei1980@163.com
 Co-Author: Xiangxiang Huang,School of Economics and Management, Southeast University, Si Pai Lou 2#, Nanjing 210096, China, xxhxin@163.com
 Xiaogan Jiang,School of Economics and Management, Southeast University, Si Pai Lou 2#, Nanjing, China, Jiangxiaogan@163.com
 Lin Zhu,School of Economics and Management, Southeast University, Si Pai Lou 2#, Nanjing, China, 1214346995@qq.com
 
Abstract: This paper investigates a three-tier supply chain network equilibrium problem. We first relate the decision makers' social responsibility with transaction decisions under the desired carbon capacity. Then we formulate the optimality of this problem as a monotone variational inequality. Next, we propose a self adaptive projection-based prediction--correction algorithm to solve the proposed model. Finally, we report the numerical results and give some analysis on the equilibrium solution.
  
Title: How to Catch a Black Swan
 Presenting Author: David Gallop,Professor Of Program Management, Defense Acquisition University, 6735 Surbiton Dr, Clifton VA 20124, United States of America, davegallop@aol.com
 
Abstract: Projects are increasingly complex. We use risk-based management to address complexity. Risk identification is the most important step in risk management because risks that are unidentified are implicitly assumed. Group dynamics such as silent dissent and group-think are weaknesses in team-based risk identification. The PreMortem technique makes it safe for the team to address risks that may otherwise go unidentified.
  
Title: Cost-effectiveness Analysis of Immunosuppression Therapy in Primary Deceased Donor Renal Transplantation
 Presenting Author: Zahra Gharibi,SMU, 5507 Stonehenge Drive, Richardson TX 75082, United States of America, zgharibi@smu.edu
 Co-Author: Mehmet Ayvaci,Assistant Professor, Naveen Jindal School Of Management, University of Texas at Dallas, 800 West Campbell Road,, Richardson TX 75080, United States of America, mehmet.ayvaci@utdallas.edu
 Michael Hahsler,Assistant Professor, Dept. Of Engineering Management, Information, And Systems, Southern Methodist University, P. O. Box 750123, Dallas TX 75275, United States of America, mhahsler@lyle.smu.edu
 Bekir Tanriover,Assistant Professor, Internal Medicine, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390, United States of America, bekir.tanriover@utsouthwestern.edu
 
Abstract: The primary cure for patients with end stage renal disease (ESRD) is kidney transplantation. In this study, we evaluate the cost-effectiveness of three common immunosuppressive induction therapies, alemtuzumab, thymoglobulin, and IL2RB as well as a no-induction strategy, from Medicare’s perspective. Using non-parametric bootstrapping method, we calculate the incremental cost-effectiveness ratios for comparing the available strategies.
  
Title: The Effect of High Socioeconomic Inequalities on Public Education Efficiency
 Presenting Author: Maria Cristina Gramani,Insper - Business Department, Rua Quatá, 300, Vila Olímpia, São Paulo SP 04546042, Brazil, mariacng@insper.edu.br
 
Abstract: A model is proposed to capture the full picture of educational efficiency in an emerging country. Because of regional discrepancies, the model uses variables related to education and to socioeconomic inequalities. The empirical results are based on data from 5,129 Brazilian municipalities and the correlation factor between the HDI-M and the educational efficiency score indicates that the HDI-M index could not capture the discrepancies of a country with high levels of socioeconomic inequality.
  
Title: Improving Scheduling and Control of the OHTC Controller in Wafer Fab AMHS Systems
 Presenting Author: Shreya Gupta,Ms/phd Student And Graduate Research Assisstant, University of Texas at Austin, Austin TX 78751, United States of America, shreya.gupta@utexas.edu
 Co-Author: John Hasenbein,Associate Professor, University of Texas at Austin, ETC 5.128B Department of Mech Engg, University of Texas at Austin, Austin TX 78712, United States of America, jhas@utexas.edu
 
Abstract: Automated Material Handling Systems (AMHS) in wafer fabs have complex requirements. Thus, a larger number of AMHS vehicles are now required to pick-up and transport these lots within the production facility. This has increased vehicular traffic jams and the wait time for lots requiring pick-up and delivery. Hence, to increase the system throughput, we present improved routing algorithms for the over hoist transport control (OHTC) system.
  
Title: An Adaptive Large Neighborhood Search Heuristic for the Inventory Routing Problem with Time Windows
 Presenting Author: Mina Hadianniasar,University of Arkansas, 901 N Pollard Street, Arlington VA 22203, United States of America, mhadiann@uark.edu
 Co-Author: Ashlea Milburn,University of Arkansas, Bell Engineering Center, Fayetteville AR 72701, United States of America, ashlea@uark.edu
 
Abstract: This research models an integrated distribution and inventory control problem (IRP) which is faced by a retail chain in the US. Currently, a direct shipping policy with time window constraints is used for replenishing stores. This paper develops an Adaptive Large Neighborhood Search Heuristic to determine the optimal timing and magnitudes of deliveries to stores. The optimal plan considers direct shipping policy as well as options combining deliveries for multiple stores into a single route.
  
Title: Forecasting-based Truck Wait Time Reduction at Logistic Nodes
 Presenting Author: Alessandro Hill,Hamburg University of Technology, Am Schwarzenbergcampus 4, Hamburg, Germany, alessandro.hill@tuhh.de
 Co-Author: Juergen Boese,Hamburg University of Technology, Am Schwarzenbergcampus 4, Hamburg, Germany, juergen.boese@tuhh.de
 Finn Meissner,Hamburg University of Technology, Am Schwarzenbergcampus 4, Hamburg, Germany, finn.meissner@tuhh.de
 
Abstract: Truck wait times at logistic nodes such as container depots, packing facilities or terminals cause delays in transport chains and traffic congestion. Truck companies and nodes experience economical losses due to vehicle idle times and a lack of planning reliability regarding routes, personnel or machinery, respectively. In this work we present a flexible forecasting-based real worldapproach using artificial neural networks to predict both, the truck wait times and the arrival rates at the nodes.
  
Title: Impact of Overbooking in Appointment Scheduling of Primary Care Services
 Presenting Author: Babak Hoseini,PhD Candidate, New Jersey institute of Technology, University Heights, Newark NJ 07102, United States of America, bh77@njit.edu
 Co-Author: Wenbo Cai,Assistant Professor, New Jersey institute of Technology, University Heights, Newark NJ 07102, United States of America, cai@njit.edu
 
Abstract: No-shows and late cancellations not only reduce the providers’ utilization, but also results in long waiting time for other patients. Overbooking has the potential to mitigate these negative impacts. However, excess overbooking may lead to even longer waiting times for patients and prolonged working days for the care team. We use a mathematical model to evaluates the benefit of overbooking and develop a scheduling policy that reduces patients' waiting time, and increase provider’s utility.
  
Title: Research on Combination of Container Yard Allocation and Automatic Lifted Vehicle Path Optimization
 Presenting Author: Hongtao Hu,Shanghai Maritime University, Room101, No 96, 555 Guzong Road, shanghai, China, hu.hongtao@foxmail.cm
 
Abstract: This paper brings in a new type of automatic transport machinery--automatic lifted vehicle which has the ability to lift container from the floor or put it down on the floor. Meanwhile, a mixed integer programming model is established to ensure that all the containers handled as far as possible in the time window. The model also considers the problem of allocating blocks to discharge containers and optimizing path of automatic lifted vehicle.
  
Title: Shipping Commodities Between a Container Terminal and Different Destination Zones Using Heavy Trucks
 Presenting Author: Mazen Hussein,Assistant Professor, University of Wisconsin-Platteville, Platteville WI 53818, United States of America, husseinm@uwplatt.edu
 
Abstract: The cost model for shipping commodities by truck developed by Hussein M. (2010) is extended to consider the impact of tollway polices on truck route selection for shipping containers of specific commodity groups near a container terminal. A path-finding model is built for this purpose. The values of time were used to mimic the truck’s choices to ship containers of different commodities between a container terminal and different facilities.
  
Title: Network Motif Analysis for an Infrastructure System Against Vulnerability
 Presenting Author: Jing Jiang,PhD, Shanghai Jiao Tong University, Shanghai, China, sjtujiangjing@163.com
 Co-Author: Xiao Liu,Professor, Shanghai Jiao Tong University, shanghai, China, x_liu@sjtu.edu.cn
 
Abstract: A motif-based evolutionary perspective is provided for infrastructure network design. First, a multi-objective vulnerability-cost model is proposed to optimize network structure. Secondly, an evolutionary algorithm is developed. Thirdly, a network is tested by structure analysis, and motifs are traced during the evolutionary process. Finally, Western States Power Grid is analyzed. Results have revealed some principles in network design towards lower cascading vulnerability and construction cost.
  
Title: Patient Reaction to Healthcare Data Breaches
 Presenting Author: Eric Johnson,Vanderbilt University, Owen School of Management, Nashville TN, United States of America, eric.johnson@owen.vanderbilt.edu
 Co-Author: Juhee Kwon,City University of Hong Kong, Business School, Hong Kong, Hong Kong - PRC, juhee.kwon@cityu.edu.hk
 
Abstract: We investigate consumer reaction to data breaches. Using a propensity score matching technique, we analyze a matched sample of U.S. hospitals. We investigate how breaches affect subsequent outpatient visits and admissions, accounting for geographically-based competition. We find that the cumulative effect of multiple breaches significantly decreases outpatient visits and admissions.
  
Title: Enhancing Distribution Performance through Improved Relationship Quality and Logistics Integration
 Presenting Author: Sung-tae Kim,Assistant Professor, SolBridge International School of Business, 128 Uam-ro, Dong-gu, Daejeon, Korea, Republic of, stkim1@solbridge.ac.kr
 Co-Author: Moon-jung Yoo,Ms., SolBridge International School of Business, 128 Uam-ro, Dong-gu, Daejeon, Korea, Republic of, myoo143@student.solbridge.ac.kr
 
Abstract: Prior research has argued that business relationship quality mediated by logistics integration has shown positively related to distribution service performance. Hence, firms attempt to achieve higher levels of logistics service and distribution service performance through logistics integration. This study examines relationship quality and logistics integration to understand how the two factors are linked to distribution service performance.
  
Title: Smart Logistics: Distributed Control of On-demand Green Transportation Services
 Presenting Author: Seokgi Lee,Assistant Professor, University of Miami, 1251 Memorial Drive 281, Coral Gables Fl 33146, United States of America, sgl14@miami.edu
 Co-Author: Yuncheol Kang,Penn State University, 236 Leonhard Building, University Park PA 16802, United States of America, yckang@psu.edu
 Vittaldas V. Prabhu,Penn State University, 348 Leonhard Building, University Park PA 16802, United States of America, vxp7@engr.psu.edu
 
Abstract: We develop a strategic decision-making framework for on-demand delivery services, considering both operational and environmental performance explained by Just-In-Time delivery service, fuel consumption, and carbon emissions. The optimal policies based on the Markov decision process are established to make admission plans of delivery requests, and an integrated dynamic algorithm for admission control and route scheduling is developed.
  
Title: Extreme-point Search Heuristics Ffr Interval-flow Generalized Network Problems
 Presenting Author: Angelika Leskovskaya,Southern Methodist University, 3145 Dyer St., Suite 372, Dallas TX 75205, United States of America, aleskovs@smu.edu
 Co-Author: Richard Barr,Southern Methodist University, 3145 Dyer St., Suite 333, Dallas 75205, United States of America, barr@lyle.smu.edu
 
Abstract: Interval-flow generalized networks are a new extension of the classic generalized network formulation that adds a conditional lower bound constraint on the arcs. An interval-pivoting heuristic that exploits the quasi-tree-forest basis structure to explore extreme points is developed and computational testing is presented.
  
Title: Hedge Fund Leverage Choice under Time-inconsistent Preference
 Presenting Author: Bo Liu,University of Electronic Science and Technology of China, No.2006, Xiyuan Ave,West Hi-Tech Zone, Chengdu SC 611731, China, b.liu07@fulbrightmail.org
 
Abstract: We show that time inconsistency preference discourages the manager from underinvesting because of the high liquidation risk. The payment of incentive fees may induce the irrational manager to be more aggressive and to overinvest.The naive manager is more conservative than the sophisticated manager and prefers a lower leverage level in normal times.Interestingly,investors are not sensitive to the manager's irrational investment behavior.
  
Title: New Assay Implementation Planning at Clinical Laboratory
 Presenting Author: Wei Liu,Industrial Engineer, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, wliu8@mdanderson.org
 Co-Author: Bedia Barkoh,Lab Coordinator, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, babarkoh@mdanderson.org
 Mylene Bole,Sr.medical Technologist, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, mdbole@mdanderson.org
 David Garcia,Data Base Coordinator, MD Anderson Cancer Center, 8515 Fannin St, Houston, United States of America, DGarcia2@mdanderson.org
 Cindy Lewing,Lab Manager, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, clewing@mdanderson.org
 Humin Lu,Senior Application System Analyst, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, HMLU@mdanderson.org
 Raja Luthra,Professor And Director, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, rluthra@mdanderson.org
 Geeta S Mantha,Operation Director Of Clinical Genomics Lab, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, GMantha@mdanderson.org
 Pramod Mehta,Supervisor, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, pmehta@mdanderson.org
 Keyur Pravincha Patel,Assistant Professor And Medical Director, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, KPPatel@mdanderson.org
 Mark Routbort,Associate Professor, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, mark.routbort@mdanderson.org
 Justin Villarreal,Data Base Coordinator, MD Anderson Cancer Center, 8515 Fannin St, Houston, United States of America, JCVillarreal@mdanderson.org
 Haobo Yang,Data Base Coordinator, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, HYang4@mdanderson.org
 Zou Zhuang,Assistant Professor And Pathologist, MD Anderson Cancer Center, 8515 Fannin St, Houston TX 77054, United States of America, ZZuo@mdanderson.org
 
Abstract: Implementation of a new complex laboratory assay at our high-volume and high-complexity clinical Molecular Diagnostics Laboratory was facilitated by application of multiple engineering approaches including workflow assessment, historical volume-based demand prediction, IT solution, and resource allocation. The new assay implementation is expected to be successful with minimal workflow interruptions, no patient care interruptions, low implementation cost and optimal resource utilization.
  
Title: Big Data Analytics for Singapore Public Train System
 Presenting Author: Nang Laik Ma,Senior Lecturer, SIM University, 461 Clementi Road, Singapore 599491, Singapore, nlma@unisim.edu.sg
 Co-Author: Beng Yee Wong,Student, Singapore Management university, 80 Stamford Rd, Singapore 178902, Singapore, bywong.2013@mitb.smu.edu.sg
 
Abstract: This paper focus on capacity planning of the Singapore public transport system. We analyse the commuters’ travelling patterns from historical transactions data. Secondly, by simulating train schedule and capacity constraints, the model mimicked the real-world situations to generate the waiting time for each commuter. Finally, a web-based visualization tool is created to provide the average waiting time for the next train at the station to enhance the commuter’s experience.
  
Title: Hospital Residents Problem: A Survey Including a New Variant
 Presenting Author: Kaitlyn Manley,College of Charleston, 66 George St, Charleston SC 29424, United States of America, manleykm@g.cofc.edu
 Co-Author: Amy Langville,College of Charleston, 66 George St, Charleston SC, United States of America, langvillea@cofc.edu
 Tyler Perini,Student, College of Charleston, 66 George St, Charleston SC 29424, United States of America, perinita@g.cofc.edu
 
Abstract: We survey several variations of the Stable Matching Problem, including the Hospital Residents Problem used to assign American medical residents to hospitals. We also present a new variation of the stable matching problem that uses an binary integer linear program to determine the minimum number of interviews that hospitals should conduct in order to still maximize the number of residents assigned.
  
Title: Exploring the Multi-objective Portfolio Tradespace
 Presenting Author: Simon Miller,Graduate Student, Penn State Applied Research Lab, PO Box 30, State College PA 16804, United States of America, ses224@arl.psu.edu
 Co-Author: Sara Lego,Research Engineer, Applied Research Lab - Penn State, P.O. Box 30, State College PA 16804, United States of America, swm154@arl.psu.edu
 Gary Stump,Research Engineer, Applied Research Lab - Penn State, P.O. Box 30, State College PA 16804, United States of America, gms158@arl.psu.edu
 Michael Yukish,Product & Process Design Dept. Head, Applied Research Lab - Penn State, P.O. Box 30, State College PA 16804, United States of America, may106@arl.psu.edu
 
Abstract: Faced with strategic choices, senior decision makers must often make trades to meet competing requirements. In collaboration with the U.S. Army, ARL has developed tools and methods to treat large scale, multi-objective optimization problems for binary portfolios with dynamic constraints. Methodology and implementation schema for real-world cases are presented, highlighting the ability to balance a combinatorial explosion of parameters in complex trades spaces with the need for timely decisions.
  
Title: Experimental Designs for Metal Detectors at Large Venues
 Presenting Author: Christie Nelson,Rutgers University, CCICADA, 4th floor, CoRE building, 96 Frelinghuysen Rd, Piscataway NJ 08854, United States of America, christie.l.nelson.phd@gmail.com
 Co-Author: Vijay Chaudhary,DIMACS, 4th floor, CoRE building, 96 Frelinghuysen Rd, Piscataway NJ 08854, United States of America, Bjchaudhary21@gmail.com
 John Edman,DIMACS, 4th floor, CoRE building, 96 Frelinghuysen Rd, Piscataway NJ 08854, United States of America, John.edman@my.wheaton.edu
 Paul Kantor,Rutgers University, CCICADA, 4th floor, CoRE building, 96 Frelinghuysen Rd, Piscataway NJ 08854, United States of America, Paul.kantor@rutgers.edu
 
Abstract: Walk-through metal detectors (WTMDs) are being used increasingly more as a security measure at large events, particularly at stadiums. Currently, WTMDs are tested using a robotic tester which tests metallic objects at level heights by sending them straight through at a constant speed. However, this is not a proper representation of how a person would enter the WTMD. We will show that the way a person walks through the WTMD impacts detection rate through our experimental results.
  
Title: ***NO SHOW***Leading Metrics for Progress Measurement and Performance Assessment in Construction Projects
 Presenting Author: Resulali Orgut,Graduate Research Assistant, North Carolina State University, Dept. of Civil, Cons. and Env. Eng., 2510 Stinson Dr., 222 Mann Hall, Raleigh NC 27695, United States of America, reorgut@ncsu.edu
 Co-Author: Mostafa Batouli,Florida International University, OHL School of Construction, College of Engineering and Computing, Miami, United States of America, sbato001@fiu.edu
 Edward Jaselskis,North Carolina State University, Dept. of Civil, Cons. and Env. Eng., Raleigh, United States of America, ejjasels@ncsu.edu
 Ali Mostafavi,Florida International University, OHL School of Construction, College of Engineering and Computing, Miami, United States of America, almostaf@fiu.edu
 Jin Zhu,Florida International University, OHL School of Construction, College of Engineering and Computing, Miami, United States of America, jzhu006@fiu.edu
 
Abstract: Progress measurement and performance assessment are critical to the management of construction projects. We perform statistical analyses to highlight key indicators for successful construction project controls by using data collected through an online survey from 27 companies. We analyze core metrics commonly used in the construction industry to develop guidelines for improving their reliability and recommend practices for interpreting metrics and indicators.
  
Title: Toward Consistent and Efficient Anomaly Detection in Hyperspectral Imagery
 Presenting Author: Todd Paciencia,USAF, AF/A9, Pentagon, Washington D.C., United States of America, todd.j.paciencia.mil@mail.mil
 
Abstract: This research will showcase development of an approach to making an unsupervised anomaly detector for Hyperspectral Imagery (HSI). The algorithm is developed to be robust to different image scenes, different sensors, and noisy spectral bands. Specifically, fusion of spectral, spatial, and Signal-to-Noise information is used, in combination with a factor analysis approach, to identify anomalies. The algorithm is shown to be desirable when compared to current state-of-the-art techniques.
  
Title: Comprehensive Performance Evaluation of High-gravity Carbonation Process in the Steelmaking Industry
 Presenting Author: Shu-yuan Pan,National Taiwan University, No 71 Chou-shan Rd., Taipei 10673, Taiwan - ROC, d00541004@ntu.edu.tw
 Co-Author: Pen-chi Chiang,National Taiwan University, No 71 Chou-shan Rd., Taipei, Taiwan - ROC, pcchiang@ntu.edu.tw
 
Abstract: An integrated portfolio of multi-waste treatment (steelmaking slag and wastewater) combined with CO2 capture in the steelmaking industry can be achieved by the high-gravity carbonation (i.e., HiGCarb) process using a rotating packed bed (RPB). In this study, the HiGCarb process was comprehensively evaluated according to engineering, environmental, and economic (3E) criteria using a cradle-to-gate life-cycle approach.
  
Title: Analysis on the Effect of Energy Efficient Technologies in Industry Sector Using Times Model
 Presenting Author: Sang Yong Park,Senior Researcher, Korea Institute of Energy Research, Yuseong-gu, Gajeong-ro 152, Daejeon 305-343, Korea, Republic of, gspeed@kier.re.kr
 Co-Author: Jong Chul Hong,Principal Researcher, Korea Institute of Energy Research, Yuseong-gu, Gajeong-ro 152, Daejeon, Korea, Republic of, jchong@kier.re.kr
 Nyunbae Park,KIER, Yuseong-go, Gajeong-ro 152, Daejeon, Korea, Republic of, park2050@kier.re.kr
 Boyeong Yun,Korea Institute of Energy Research, Yuseong-gu, Gajeong-ro 152, Daejeon, Korea, Republic of, yunboyeong@kier.re.kr
 
Abstract: The South Korea established energy policy which is focusing demand management rather than energy supply to secure a stable energy supply and to cope with climate change efficiently through 2nd national energy basic plan in 2014. This research developed energy system model which can analyze the effect of energy efficient technologies on demand management based on TIMES(The Integrated MARKAL-EFOM System) model and conducted case study on industry sector in Korea.
  
Title: The Humility Project: NMF and Other Matrix Factorizations for Textual Analysis
 Presenting Author: Tyler Perini,Student, College of Charleston, 66 George St, Charleston SC 29424, United States of America, perinita@g.cofc.edu
 Co-Author: Amy Langville,College of Charleston, 66 George St, Charleston SC, United States of America, langvillea@cofc.edu
 
Abstract: This is one of the first studies on the use of matrix decompositions as the primary engine for describing and predicting psychological characteristics in a corpus of language data. With text parsing tools, large written samples are parsed into a sparse matrix. A low-rank matrix factorization of a weighted version of this matrix is then used to determine which documents are humble and which are not humble. Three factorizations, the SVD, NMF, and weighted NMF, are compared.
  
Title: Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty
 Presenting Author: Junjie Qin,Ph.d. Candidate, Stanford University, 126 Blackwelder Ct, 1004, Stanford CA 94305, United States of America, jqin@stanford.edu
 
Abstract: The optimal control of energy storage networks in stochastic environments is an important open problem. This paper provides an efficient algorithm to solve this problem with performance guarantees. A sub-optimality bound for the algorithm is derived which can be minimized by solving a semidefinite program. Distributed implementation is derived based on alternating method of multipliers. Numerical examples verify our theoretical performance bounds and demonstrate the scalability of the algorithm.
  
Title: Should Retailers Adopt 3d Printing?
 Presenting Author: Sharareh Rajaei Dehkordi,PhD Candidate, New Jersey Institute of Technology, University Heights, Newark NJ 07102, United States of America, sr552@njit.edu
 Co-Author: Wenbo Cai,Assistant Professor, New Jersey institute of Technology, University Heights, Newark NJ 07102, United States of America, cai@njit.edu
 
Abstract: Should retailers provide 3D printing services in addition to the traditional off-the-shelf product? We answer the question by examining retailers’ optimal joint decisions on his inventory management policy and pricing scheme while considering consumers’ heterogeneous preferences for self-designed, 3D printed products vs. off-the-shelf products. We use a multi-server queue with limited capacity to capture customers' production selection process and its impact on the retailer's expected profit.
  
Title: Stochastic Network Design with Decision-dependent Uncertainties
 Presenting Author: Nathaniel Richmond,University of Iowa, 14 MacLean Hall, Iowa City IA 52242, United States of America, nathaniel-richmond@uiowa.edu
 
Abstract: Little research has been conducted on stochastic network design problems in which the probability distribution of future random events is affected by prior actions. However, such problems are ubiquitous and important. For example, planned reinforcements of a power network directly influence which nodes are more likely to fail. We present a stochastic two-stage programming model with decision-dependent uncertainties, discussing solution methods for the associated unique computational challenges.
  
Title: Scheduling Part-time Employees with Interactive Optimization
 Presenting Author: Robert Rose,President, Optimal Decisions LLC, 4 Kirby Lane, Franklin Park NJ 08823, United States of America, robertl.rose@verizon.net
 
Abstract: Many employee scheduling problems are very challenging: they are hard combinatorial optimization problems that contain multiple objectives and 'soft' constraints. Such problems do not lend themselves to a pure optimization approach. A ‘Human Centered’ approach, will be described: an initial schedule is generated analytically through a series of heuristic procedures, and a final schedule is produced using an interactive graphics module. A prototype scheduling program will be demonstrated.
  
Title: ***LATE CANCELLATION 10-27***Fast, Provable Algorithms for Isotonic Regression in All Lp-norms (to Appear At Nips 2015)
 Presenting Author: Sushant Sachdeva,Postdoctoral Associate, Yale University, Yale Institute of Network Sciences, P O Box 208263, New Haven CT 06520, United States of America, sachdevasushant@gmail.com
 Co-Author: Rasmus Kyng,Yale University, Dept of Computer Science, 51 Pro, New Haven CT 06511, United States of America, rasmus.kyng@yale.edu
 Anup Rao,Georgia Institute of Technology, College of Computing, North Avenue, Atlanta GA, United States of America, anup.rao@yale.edu
 
Abstract: Given a directed acyclic graph G, and values y on the vertices, the Isotonic Regression of y is a vector x that respects the partial ordering given by G, and minimizes ||x - y||, for a given norm. We present improved algorithms for Isotonic Regression for all weighted Lp norms, with rigorous performance guarantees. Our algorithms combine interior point methods with provable fast solvers for the associated linear systems. The algorithms are practical and lend themselves to fast implementations.
  
Title: Mathematical Modelling and Analysis of New Zealand Legislation Network
 Presenting Author: Neda Sakhaee,University of Auckland, 38 Princes Street, Auckland, New Zealand, nsak206@aucklanduni.ac.nz
 
Abstract: In 2015 the concept of Legislation Network is proposed as a mathematical tool for studying the current and future status of the legislation system in European Union. Unlike perhaps the relations between documents are at least as important as the content. This type of network has some novel features which make it an excellent test case for new network science tools.
  
Title: Deadhead Selection Strategies for Crew Recovery
 Presenting Author: Sujeevraja Sanjeevi,Senior Operations Research, Sabre Holdings, 3150 Sabre Drive, Southlake TX 76092, United States of America, sujeevraja.sanjeevi@sabre.com
 Co-Author: Chunhua Gao,Sabre Holdings, 3150 Sabre Drive, Southlake TX 76092, United States of America, chunhua.gao@sabre.com
 Helder Inacio,Senior Operations Research, Sabre Holdings, 3150 Sabre Drive, Southlake TX 76092, United States of America, helder.inacio@sabre.com
 
Abstract: Crew recovery is the problem of minimizing the impact of a disruption to an airline by getting disrupted crews back on plan while minimizing incurred costs. Deadheads are flights that transport crew members as passengers and are a critical part of crew recovery. Consideration of all available deadheads to recovery makes problem sizes prohibitive. We present a few deadhead selection strategies that significantly improve solution quality without impacting run-time for real-world scenarios.
  
Title: Talk is Cheap - Action is Expensive
 Presenting Author: Simone Schmid,University of Chemnitz, Huebschmanntrasse 24, Chemnitz 09112, Germany, simone.schmid@wirtschaft.tu-chemnitz.de
 Co-Author: Peter Pawlowsky,Chemnitz University of Technology, p.pawlowsky@wirtschaft.tu-chemnitz.de
 
Abstract: Adequate response to uncertain and unpredictable environmental changes requires innovative, agile, and adaptive team competencies. We use an interdisciplinary approach to assess and evaluate team competencies. From theory and previous research we derive indicators and test these by training teams accordingly. Experimental groups were given theoretical and practical trainings with regard to these team competencies. Control groups acted as usual. A succeeding standardized simulation in a high fidelity simulation environment showed significant effects with regard to team performance. From these results we propose behavioral markers for team competencies that can be used to assess team performance in critical situations.
  
Title: Euro/Roadef Challenge
 Presenting Author: Tejinder Singh,Air Liquide, 12800 W. Little York Rd, Houston TX, United States of America, tejinder.singh@airliquide.com
 Co-Author: Jean Andre,Air Liquide, 1 chemin de la Porte des Loges, Les Loges-En-Josas 78350, France, jean.andre@airliquide.com
 Jeffrey Arbogast,Air Liquide, 200 GBC Dr, Newark DE 19702, United States of America, jeffrey.abrogast@airliquide.com
 Rodrigue Fokouop,Air Liquide, 1 chemin de la Porte des Loges, Les Loges-En-Josas, France, rodrigue.fokouop-w@airliquide.com
 Michele Quattrone,Air Liquide, 1 chemin de la Porte des Loges, Les Loges-En-Josas, France, michele.quattrone@airliquide.com
 
Abstract: The French OR Society (ROADEF) along with EURO, periodically organizes an OR challenge dedicated to industrial applications. This year, Air Liquide proposes the challenge problem concerning an IRP for the bulk distribution of liquefied gases. The challenge is open to everyone and will be presented during the EURO 2015 in Glasgow, Scotland in July 2015 and the results will be announced at EURO 2016 in Poznan, Poland. Prizes totaling 20,000 Euros will be awarded to the best teams.
  
Title: An Optimization Approach to Warehouse Line Striping
 Presenting Author: Sudharshana Srinivasan,Research Scientist, Altria Client Services, 601 E. Jackson St., Richmond VA 23219, United States of America, sudharshana.srinivasan@altria.com
 Co-Author: David Kane,Associate Principal Scientist, Altria Client Services, 601 E. Jackson St.,, Richmond VA 23219, United States of America, David.B.Kane@altria.com
 
Abstract: We present a mixed-integer programming model to optimize product storage at an industrial warehouse, while adhering to safety standards stipulated by the county and the business. The model is applied to a tobacco warehouse and the results provide a storage solution comparable to current practice with an improved operational efficiency. The model recommends more walking aisles to facilitate increased spacing and airflow around the product; both of which are valued business objectives.
  
Title: Applications Of Genetic Algorithms For Simulation-based Healthcare Optimization
 Presenting Author: Cory Stasko,MIT, 4 Garden Court, Apt #4, Cambridge MA 02138, United States of America, cstasko@mit.edu
 
Abstract: We apply genetic algorithms to three distinct cases of highly non-linear healthcare optimization problems. In the first problem, OR schedules are designed to minimize downstream bottlenecks. The second problem involves network management for an accountable care organization. The third problem involves promoting the spread of ideas among connected professionals. In each case, the objective (fitness) function is the output of a simulation, and a brute force solution search is not feasible.
  
Title: How Do We Capture the Potential Risk of Intravenous Drug Infusion using Alert Data?
 Presenting Author: Wan-ting Su,Graduate Student, Purdue University, 3376 Peppermill Drive, West Lafayette IN 47906, United States of America, su33@purdue.edu
 Co-Author: Poching Delaurentis,Purdue University, 610 Purdue Mall, West Lafayette in 47907, United States of America, poching@purdue.edu
 Mark Lehto,Purdue University, 315 N. Grant St., West Lafayette in 47907, United States of America, lehto@purdue.edu
 
Abstract: The use of smart infusion pumps is one such mechanism in ensuring the safety of medication infusions in clinical settings. We aim to utilize the data of different alert types from the Infusion Pump Informatics system to capture averted or potential medication errors and define and determine the overall risk of potential harm within a certain period of time in a medical facility. Our analysis can be used as a measure in improving intravenous medication safety and infusion drug-delivery process.
  
Title: Developing Freeway Demand Estimation Alternatives with Mixed Integer Linear Programming
 Presenting Author: Joseph Trask,North Carolina State University, 909 Capability Drive, Raleigh NC, United States of America, jltrask@ncsu.edu
 Co-Author: Behzad Aghdashi,Institute for Transportation Research and Education - NCSU, 909 Capability Drive, Raleigh NC, United States of America, behzad_aghdashi@ncsu.edu
 John Baugh,North Carolina State University, 909 Capability Drive, Raleigh NC, United States of America, john.baugh@ncsu.edu
 Nagui Rouphail,Institute for Transportation Research and Education - NCSU, 909 Capability Drive, Raleigh NC, United States of America, rouphail@ncsu.edu
 
Abstract: This research presents a Mixed Integer Linear Programming optimization model for traffic demand estimation based on the methodology developed in the Highway Capacity Manual (HCM). Due to a lack of uniqueness for solution demand sets, a Modeling to Generate Alternatives (MGA) approach is developed to investigate the wide ranges of optimal solution sets. These solution sets can be compared through their effects on intermediate performance measures and sensitivity analysis.
  
Title: Batch Testing of a Series System
 Presenting Author: Tonguç Ünlüyurt,Sabanci University, Orhanli, Tuzla, Istanbul, Turkey, tonguc@sabanciuniv.edu
 Co-Author: Rebi Daldal,Sabanci University, Orhanli, Tuzla, Istanbul, Turkey, rebi@sabanciuniv.edu
 Ozgur Ozluk,Bogazici University, Bebek, Istanbul, Turkey, ozgur@sfsu.edu
 Baris Selcuk,Bahcesehir University, Besiktas, Istanbul, Turkey, baris.selcuk@bahcesehir.edu.tr
 Zahed Shahmoradi,Sabanci University, Orhanli, Tuzla, Istanbul, Turkey, zahedshahmoradi@sabanciuniv.edu
 
Abstract: We consider the problem of determining the correct value of an AND function when it is costly to learn the values of its variables, with the minimum expected cost. We refer to a subset of variables whose values can be learnt at the same time a meta-test. The cost of learning the values of the variables in a meta-test includes a fixed cost plus the costs of the tests in the meta-test.
  
Title: Shape-preserving L1 Spline Fits: Calculation and Capability
 Presenting Author: Ziteng Wang,Department of Industrial and Systems Engineering, North Carolina State University, 3120 Walnut Creek Parkway, Apt. E, Raleigh NC 27606, United States of America, zwang23@ncsu.edu
 Co-Author: Shu-cherng Fang,North Carolina State University, Daniels 450, North Carolina State University, Raleigh NC 27695, United States of America, fang@ncsu.edu
 
Abstract: L1 spline fits have been developed over the past decades to approximate multi-scale data and have been shown to preserve shapes well. Local approaches are designed for efficient calculation. Quantitative measures are proposed to evaluate the shape-preserving capability of different types of L1 spline fits.
  
Title: Evolutionary Optimization Tools of Nanostructures for Solar Cells
 Presenting Author: Baomin Wang,University of Pittsburgh, 1048 Benedum Hall 3700 O’Hara Street, Pittsburgh PA 15261, United States of America, baw57@pitt.edu
 
Abstract: Simulation plays a significant role in optimizing solar cell efficiency. Current used optimization is exhaust search, only feasible for small group of parameters, 3 or 4. But for 7 or 8, it takes months. In this work, we integrate genetic algorithm with FDTD methods to optimize the nanostructure. This evolutionary method can decrease the simulation time to 1/6 of original time. This work demonstrates the ability of genetic algorithm technique to quickly search through a large parameter space.
  
Title: Surgical Operations Scheduling with Machine Eligibility and Resource Constraint
 Presenting Author: Shan Wang,Shanghai Jiaotong Univerisity, 704 West 180th Street, First Floor, #4, New York City NY 10033, United States of America, wangshan_731@sjtu.edu.cn
 Co-Author: Huiqiao Su,Shanghai Jiaotong Univerisity, 1954 Huashan Road, Xuhui Dist, Zhongyuan 111, Shanghai SH 200030, China, qiaomai89@126.com
 Guohua Wan,Prof., Shanghai Jiaotong Univerisity, 1954 Huashan Road, Xuhui Dist, Antai College of Econ.&Mngt., Shanghai SH 200030, China, ghwan@sjtu.edu.cn
 
Abstract: We study a problem in surgical operations scheduling and model it as a resource-constrained machine scheduling problem with eligibility restriction to minimize the makespan. By decomposing it into two subproblems, we develop effective heuristic algorithms to solve the problem. We test the proposed algorithms on randomly generated instances as well as real data set from a large hospital. The numerical results show the effectiveness and potential practical value of the models and the algorithms.
  
Title: Optimizing System-Level Preventative Maintenance Cost of Multistate Series-Parallel Systems
 Presenting Author: Sallamar Worrell,The George Washington University, 3117 Icehouse Place, Bryans Road MD 20616, United States of America, skaw7@gwu.edu
 Co-Author: Steve Doskey,The George Washington University, 950 North Glebe Road, Suite 118, Arlington VA 22203, United States of America, sdoskey@gwmail.gwu.edu
 James Moreland Jr.,The George Washington University, 950 North Glebe Road, Suite 118, Arlington VA 22203, United States of America, jmorelan@email.gwu.edu
 
Abstract: Maintenance costs for complex systems are often overpaid due to the lack of maintenance harmony between the individual subsystems. The research in this study proposes the use of a new meta-heuristic optimization method, the Grey Wolf Optimizer algorithm developed by Mirjalili and Lewis, to identify the optimal system-level maintenance strategy for multistate series-parallel systems and aims to produce better results than the methods previously applied to this problem in published literature.
  
Title: ***NO SHOW***Predicting Digital Currency Price from Social and Traditional Media
 Presenting Author: Peng Xie,Georgia Institute of Technology, Room 907, 100 10th Street, Atlanta GA 30309, United States of America, peng.xie@scheller.gatech.edu
 
Abstract: Using daily Bitcoin price data and Bitcoin Forum discussion, we try to understand if social media can affect Bitcoin price and how long does it take. We use the percentage of negative words as the measure of the article sentiment. The results show that social media can affect price. However, for information sources focusing on speculation, the effects on prices are immediate. In contrast, information concerning fundamentals impacts prices in a longer holding period.
  
Title: The Dimensions of Supervision-subordinate Relationship
 Presenting Author: Liuqing Yang,Xi`an Jiaotong University, No.28, Xianning West Road, Xi'an, China, ylq2011@stu.xjtu.edu.cn
 Co-Author: Qiaozhuan Liang,Xi`an Jiaotong University, No.28, Xianning West Road, xi'an, China, sibell@mail.xjtu.edu.cn
 
Abstract: Subordinate can form distinguishable social exchange relationships with their immediate supervisor.The exchange resources differ between organizational and personal. Based on the taxonomy, social exchange relationship can development a construct of four dimensions: work, flatter, private, selfless. Various dimension have different impact on performance as a mediator or intervening variable. The construct can explain the puzzle of relationship between social exchange relationship and performance.
  
Title: Counterfeits, Anti-counterfeit Technology and Monitoring Strategy
 Presenting Author: Shiqing Yao,The Chinese University of Hong Kong, 9/F, Cheng Yu Tung Building, No.12 Chak Cheung Street, Shatin, N.T., Hong Kong, Hong Kong - PRC, sqyaocuhk@gmail.com
 Co-Author: Kaijie Zhu,Associate Professor, The Chinese University of Hong Kong, 9/F, Cheng Yu Tung Building, No.12 Chak Cheung Street, Shatin, N.T., Hong Kong, Hong Kong - PRC, kzhu@baf.cuhk.edu.hk
 
Abstract: We consider an authentic company that sells its products to a customer market. In the same market, a counterfeiter may sell its low-quality counterfeits. The authentic company can put effort into developing an anti-counterfeit technology to distinguish its products from counterfeits while the authority can monitor the market and outlaw counterfeiting localities. We derive the company's optimal decision on its anti-counterfeit effort and highlight its difference from conventional wisdom.
  
Title: Optimization of Area Traffic Control: A Binary Mixed Integer Linear Programming Approach
 Presenting Author: Zhao Zhang,Research Assistant, Tsinghua University, Room 615, Shunde Building, Haidian District, Beijing 100084, China, zzaxx@tsinghua.edu.cn
 
Abstract: This paper proposes a model aims at optimizing area traffic control. We use network total delay as the objective in the model. In this research, cell transmission model is used to discretize research time into many intervals and signal coordination, lane settings, phase, start of green and green split can be optimized simultaneously. The model is linear in nature and can be solved by standard branch and bound algorithm.
  
Title: Identify Naturally Occurring Healthcare Provider Referral Networks for Diabetic Patients
 Presenting Author: Yuchen Zheng,PhD Student, Georgia Institute of Technology, Atlanta GA 30032, United States of America, richardzyc@gatech.edu
 Co-Author: Kun Lin,IBM, 1101 Kitchawan Rd, Yorktown Height NY 10598, United States of America, klin@us.ibm.com
 Jeremy Pickreign,CDPHP, 500 Patroon Creek Blvd, Albany NY 12206, United States of America, Jeremy.Pickreign@cdphp.com
 Thomas White,CDPHP, 500 Patroon Creek Blvd, Albany NY 12206, United States of America, Thomas.White@cdphp.com
 Gigi Yuen,IBM, 3031 N Rocky Point Dr West, Tampa FL 33607, United States of America, gigi.yuen@us.ibm.com
 
Abstract: The pioneer Accountable Care Organizations (ACOs), where doctors voluntarily form groups to deliver coordinated quality care, saved Medicare $400 million in two years. To improve ACOs design, we utilize past care patterns and adopt modularity maximization to detect pre-existing referral networks for diabetic patients, within which doctors share patients frequently. We further identify the driving forces of the underlying community structures and understand the relation to cost and utilization.
  
Title: Real-time Heat Exchanger Efficiency Monitoring
 Presenting Author: Yousif Abualsoud,Saudi Aramco, Al-Midra, Dhahran, Saudi Arabia, yousif.abualsoud@aramco.com
 
Abstract: Saudi Aramco Engineering Services developed a systematic model to calculate shell and tube heat exchangers efficiency in real time using data analytics technique. Monitoring the heat exchanger efficiency in real time supports the decisions making to plan for turndown time by detecting the failure time proactively. Moreover, it provides the field engineers continuous monitoring to energy consumer and highlights the wasted energy locations, quantity and cost.
  
Title: A Decision-analytic Approach to Inferring Preference from Choice Behavior
 Presenting Author: Matthew D. Wood,Research Psychologist, US Army Engineer Research & Development Center, Concord MA, United States of America, Matthew.D.Wood@usace.army.mil
 Co-Author: Matthew Bates,US Army Corps of Engineers, 696 Virginia Rd, Concord, United States of America, Matthew.E.Bates@usace.army.mil
 Danielle M. Beeler,
 Jeffrey M. Keisler,
 
Abstract: Decision making in resource management requires consideration of multiple conflicting objectives. Traditional elicitation methods (e.g., swing weighting) work well with clearly defined problem spaces and effects between decisions and consequences. In more complex domains, an inferential approach is needed to estimate preference using system feedback over samples with subject-matter experts. We describe a decision analysis game with an environmental case study problem.
  
Title: Artificial Variability and Case Mix in Relation to Patient Flow at a Hospital Outpatient Clinic
 Presenting Author: Monique Bakker,Phd Candidate, City University of Hong Kong, Flat B 2/F Mo Kwan House, 438 Portland Street, Hong Kong - 999077, Hong Kong - ROC, moniquebakker121@gmail.com
 
Abstract: We aim to improve the patient flow through first, second, and nth visits to a specialist outpatient clinic and elective surgery. We investigate variability in key resource availability (i.e. the specialists) in relation to case mix decisions, sub-specialization restrictions, and resource allocation: how is indirect wait time (or access time). We use Discrete Event Simulation to schedule patients under a broad and realistic set of rules and restrictions to compare alternate scenarios.