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SB06 ■ SB06 06- West 103 B- CC Analysis of Steady-State Simulation Output Processes Sponsor: Simulation Sponsored Session Chair: Emily Lada, Operations Research Specialist, SAS, SAS Campus Dr., Cary, NC, 27513, United States of America, Emily.Lada@sas.com 1 - Evaluation of Batched Quantile Estimation Methods Dave Goldsman, Georgia Institute of Technology, School of ISYE, Atlanta, GA, 30332, United States of America, sman@gatech.edu, Christos Alexopoulos, James Wilson We study the performance of asymptotically valid confidence intervals (CIs) methods for steady-state quantiles computed from nonoverlapping batches. Our results form the basis for the development of fully sequential procedures that yield CI estimators of steady-state quantiles with user-specified absolute or relative precision. 2 - Initialization of Finite-horizon Simulations Peter Glynn, Professor, Stanford University, Huang Engineering Center, Stanford, CA, 94305, United States of America, glynn@stanford.edu, Eunji Lim We introduce a new type of initialization problem that arises in real-time simulations. In such applications, the state needed to initialize the simulation is not completely observable, either because monitoring the physical system does not provide complete information or because the model includes artificial states that are not observable. We discuss the new initialization issues, make connections to the filtering literature, and present two algorithms to address these issues. 3 - The Simulation Start-up Problem: Performance Comparison of Recent Solution Procedures James Wilson, Professor, Edward P. Fitts Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695- 7906, United States of America, jwilson@ncsu.edu, Anup Mokashi, Emily Lada We summarize the results of a comprehensive experimental performance comparison of some recent procedures for solving the simulation start-up problem, including the methods incorporated in MSER-5, N-Skart, waSSP, and SBatch. Substantial differences in performance are observed, especially in comparisons of MSER-5 with the latter three procedures. ■ SB07 07- West 104 A- CC INFORMS DM Student Paper Award Competition Sponsor: Data Mining Sponsored Session Chair: Peter Qian, University of Wisconsin, Madison, WI, United States of America, peterq@stat.wisc.edu 1 - INFORMS Data Mining Best Student Paper Competition Peter Qian, University of Wisconsin, Madison, WI, United States of America, peterq@stat.wisc.edu Four selected finalists will present their papers in the INFORMS DM Best Student Paper competition. The winner will be announced at the INFORMS DM business meeting and all finalists will receive an award certificate. ■ SB08 08- West 104 B- CC Joint Session Doing Good with Good OR/SPPSN: Doing Good with Good OR Competition: Finalist Presentations I Cluster: Doing Good with Good OR Student Competition & Public Programs, Service and Needs Invited Session Chair: Sila Cetinkaya, Texas A&M University, College Station, TX, United States of America, sila@tamu.edu INFORMS Phoenix – 2012 82 1 - The Effect of Budgetary Restrictions on Breast Cancer Diagnostic Decisions Mehmet Ayvaci, Assistant Professor, The University of Texas at Dallas, Jindal School of Management, 800 West Campbell Road, Richardson, TX, 75080, United States of America, ayvaci@wisc.edu, Elizabeth Burnside, Oguzhan Alagoz We develop a finite-horizon constrained Markov Decision Process to model diagnostic decisions after mammography where we maximize the total expected quality adjusted life years (QALYs) of a patient under resource constraints. Comparing to actual clinical practice, using optimal thresholds may result in 22% cost savings without sacrificing QALYs. Our modeling framework could be used for evaluating cost-effectiveness of diagnostic procedures. 2 - Dynamic Monitoring of Chronic Disease Jonathan Helm, Assistant Professor, Indiana University, Kelley School of Business, ODT, 1309 East Tenth Street, Bloomington, IN, 47405, United States of America, jhelm@umich.edu, Gregg Schell This research develops new methods for dynamically monitoring chronic disease to allow better detection of disease worsening with fewer tests. We developed a prototype and tested it on a major clinical trial with results that significantly outperform current practice. Our team, including engineers, a clinician, and an epidemiologist, is working toward integrating our algorithms into widely used glaucoma testing machines. 3 - Optimal Distribution of Medical Backpacks and Health Surveillance Assistants in Malawi Amber Kunkel, Rice University, 6100 Main Street, Houton, TX, 77005, United States of America, agkunkel@gmail.com, Elizabeth Van Itallie, Duo Wu The Malawian people face severely limited healthcare access. To address this issue, we used large-scale p-median and capacitated facility location problems to create a scalable, three-tiered plan for optimal allocation of Health Surveillance Assistants (HSAs), HSA designated medical backpacks, and backpack resupply centers in Malawi. This plan will be used to direct the Beyond Traditional Borders’ HSA backpack program scale-up. ■ SB09 09- West 105 A- CC Neurophysiology and Decision Making Sponsor: Multiple Criteria Decision Making Sponsored Session Chair: Niklas Ravaja, Professor, Aalto University, School of Economics, P.O. Box 21255, Helsinki, 00076, Finland, ravaja@mappi.helsinki.fi 1 - Neurophysiological Methods in Decision Making Research Niklas Ravaja, Professor, Aalto University, School of Economics, P.O. Box 21255, Helsinki, 00076, Finland, ravaja@mappi.helsinki.fi, Pekka Korhonen, Outi Somervuori, Jyrki Wallenius, Murat Koksalan Neurophysiological or psychophysiological measures, such as electroencephalography (EEG), facial electromyography (EMG), electrocardiography (ECG), and electrodermal activity (EDA), have attained increasing attention in studying emotional and cognitive processes during decision making. This presentation will discuss the use of these measures. In addition, some recent decision making studies employing neurophysiological measures will be presented. 2 - Purchase Behavior and Psychophysiological Responses to Different Price Levels Outi Somervuori, Aalto University School of Economics, 00076, Finland, outi.somervuori@aalto.fi, Niklas Ravaja The aim of the study was to examine emotional processes in purchase decision. The participants were presented purchase decision trials with 14 different products whose price levels were changed while their facial electromyography (EMG) and electrodermal activity (EDA) were recorded. The results suggest that low prices and national brand products induce higher positive emotions compared to high prices and private label products. Also, positive emotions are related to greater purchase intent.
■ SB10 10- West 105 B- CC A Robust Optimization Approach to Stochastic Analysis Sponsor: Optimization/Stochastic Programming Sponsored Session Chair: Nataly Youssef, Graduate Student, Massachusetts Institute of Technology, 143 Albany St., Apt. 014C, Cambridge, MA, 02139, United States of America, youssefn@mit.edu 1 - Robust Queueing Theory Chaithanya Bandi, PhD Student, Massachusetts Institute of Technology, 02139, United States of America, cbandi@mit.edu, Nataly Youssef, Dimitris Bertsimas We study queueing systems by employing robust optimization as opposed to stochastic analysis. We set the limiting laws of probability as the axioms of our approach and model queue primitives by uncertainty sets. We analyze single-class multi-server queueing networks and obtain closed form expressions for the waiting times with heavy-tailed arrival and service processes. Our approach yields accurate results compared to simulations and is fairly insensitive to network size and traffic intensity. 2 - Network Information Theory via Robust Optimization Dimitris Bertsimas, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, United States of America, dbertsim@mit.edu, Chaithanya Bandi We provide via robust optimization (RO) inner and outer bounds for the capacity region of multi-user channels with interference for finite code length n and a code that matches the inner bound. As n increases,the bounds are tight and lead to an asymptotic characterization of the capacity region which is a well-known open problem. The RO problems take the form of rank minimization SDPs for Gaussian and MILPs for Exponential, Binary and Uniform channels. We report results for up to 200000 codewords. 3 - Pareto Efficiency in Robust Optimization Nikos Trichakis, Assistant Professor, Harvard Business School, Boston, MA, United States of America, ntrichakis@hbs.edu, Dan Iancu We argue that the classical robust optimization (RO) paradigm need not produce solutions that possess the (suitably adapted) property of Pareto optimality. We illustrate how this could lead to inefficiencies and suboptimal performance in practice. We introduce and provide a basic theoretical characterization of Pareto robustly optimal solutions. Numerical studies demonstrate that such solutions have significant upside compared with ones obtained via classical RO, at no extra cost or downside. ■ SB11 11- West 105 C- CC Application of Stochastic Programming I Contributed Session Chair: Yang Tan, FedEx Services, 3640 Hacks Cross Rd., Memphis, TN, 38125, United States of America, ytan0920@gmail.com 1 - A Scenario Generation-based Lower Bounding Approach for Stochastic Scheduling Problems Lingrui Liao, Google Inc., 1550 Technology Dr., Unit 3085, San Jose, Ca, 95110, United States of America, lingrui@gmail.com, Hanif D. Sherali, Subhash C. Sarin We investigate scenario generation methods to establish lower bounds on the optimal objective value of stochastic scheduling problems. In contrast to the Sample Average Approximation approach, we use the idea of recursive stratified sampling to develop a discrete bounding method. Exact lower bounds for expectation and conditional value-at-risk objectives are developed, and are demonstrated using a single machine total weighted tardiness problem with experimental results. 2 - A Stochastic Programming Approach for Decision-dependent Uncertainty in Production Planning Alwin Haensel, Université Paris Sud, Bât 650 Université Paris-Sud 11, Orsay, 91405, France, haensel.alwin@gmail.com, Marco Laumanns Regulation pressure on production quality and standards is increasing. A production plan needs to consider risks of failing the inspections, whose realizations dependents on the production schedule. This dependency increases the complexity significantly. The uncertain inspection realizations are modeled by scenarios generated from given product-site hazards. We propose a general scenario based stochastic programming approach to compute solutions for riskneutral and risk-averse decision makers. INFORMS Phoenix – 2012 83 3 - Stochastic Approach for Resource Allocation and Facility Utilization Anirudha Kulkarni, Graduate Research Assistant, Rochester Institiute of Technology, Rochester, Rochester, NY, 14623, United States of America, apk2932@rit.edu, Scott Grasman, Shrikant Jarugumilli We formulate a stochastic resource allocation model that considers fluctuating demand over a long planning horizon. The stochastic program includes hiring, firing, overtime, shift-swapping and cross training. The rationale behind this is to reduce gaps in assignments and ensure efficient resource utilization. Results include discussion of the recourse, value of the stochastic solution, and implementation. 4 - Stochastic Lot-Sizing Model for Deteriorating Items under Partial Backlogging Yang Tan, FedEx Services, 3640 Hacks Cross Rd., Memphis, TN, 38125, United States of America, ytan0920@gmail.com This research is distinguished from most literature by considering the effects of deterioration and partial backlogging under stochastic customer demand. The optimal conditions under which a (s, S) policy holds are successfully derived and the explicit order quantities are obtained by reformulating the problem as a stochastic programming model. 5 - Linear Profile Monitoring Azadeh Adibi, Arizona State University, 1265 E. University Dr, Tempe, AZ, United States of America In this study,a method is proposed for phase 2 monitoring of linear profiles. Also, performance of the proposed method is compared with an existing method based on average run length criterion under different shifts in the model parameters. ■ SB12 SB12 12- West 106 A- CC Structure of Convex Integer Programs Sponsor: Optimization/Integer Programming Sponsored Session Chair: Marco Molinaro, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, United States of America, molinaro@cmu.edu 1 - Closedness of Mixed Integer Hulls of Second Order Conic Programming Problems Diego Moran, Georgia Tech, 755 Ferst Drive NW, Room 422, Main building, Atlanta, GA, 30332, United States of America, dmoran@gatech.edu, Santanu Dey Given rational matrices $A$, $B$ and vector $b$, we show that there exists a polynomial time algorithm to check the closedness of the convex hull of the set $\{(x,y)|Ax +By -b \in L, x integral\}$, where $L$ is the Lorentz cone. Moreover, in the special case of pure integer problems, we present sufficient conditions for verifying the closedness of the integer hull of the feasible region of a more general second order conic programming problem (SOCP) that can also be checked in polynomial time. 2 - Disjunctive Cuts for Convex Mixed Integer Nonlinear Programs (MINLP)s and Extended Formulations Mustafa Kilinc, Postdoctoral Researcher, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, United States of America, mrk46@pitt.edu, Sina Modaresi, Jeff Linderoth, James Luedtke, Juan Pablo Vielma In this work, we study positive effects of extended formulations on generating cutting planes for convex MINLPs. First, stronger cuts can be generated in an extended formulation. Second, the performance of a pure LP-based cut generation method can be improved via extended formulations. 3 - On the Relative Strength of Different Generalizations of Split Cuts Marco Molinaro, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, United States of America, molinaro@cmu.edu, Sanjeeb Dash, Oktay Gunluk In this paper we show the complete relationship between the split, cross, crooked cross and t-branch split closures. We also study the strength of cross cuts from basic and 2-row relaxations. This answers three open questions left open by Day, Dash and Gunluk (2010).
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