2015 Informs Annual Meeting

POSTER SESSION

INFORMS Philadelphia – 2015

20 - Rocket Stage Optimization in Kerbal Space Program Nathan Arrowsmith, Rochester Institute of Technology, 2800 Butternut Lane, Canandaigua, NY, 14424, United States of America, nea4305@rit.edu 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. 21 - Investigation of the Effect of Location, Built Environment and Urban Forms on Customer Satisfaction Homa Atefyekta, Sharif University of Technology, No.14, 5th St., South Piruzan st, Tehran, 1466643479, Iran, homa.atefyekta@gmail.com, Hamed Ahangari, Hoda Atef Yekta 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. 22 - What do Equity Hedge Funds Really do? Evidence in the QE Period Geum Il Bae, KAIST, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea, Republic of, gi_bae@kaist.ac.kr, Sun Young Park, Woo Chang Kim 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 Rosemary T. Berger, University of Wisconsin - Madison, 330 N. Orchard St., Madison, WI, 53715, United States of America, rosemary.t.berger@gmail.com, Michael Ferris, Jeff Linderoth 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. 24 - Provable Submodular Function Minimization via Wolfe’s Algorithm Deeparnab Chakrabarty, Dr, Microsoft, 9 Lavelle Road, Bangalore, India, deeparnab@gmail.com 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. 25 - Stochastic PDE-constrained Optimization of Vibrations of a Plate under a Piecewise-linear Current Dmitry Chernikov, The University of Iowa, 1010 W Benton St. 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. 26 - Assessing Kernel-based Anomaly Detection Algorithms Hyun-chang Cho, Seoul National University, Banpo-gu, Seocho-dong, Seoul, Korea, Republic of, hccho@dm.snu.ac.kr, Sungzoon Cho 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. #208F, Iowa City, IA, 52246, United States of America, scher.de@gmail.com, Pavlo Krokhmal, Olesya Zhupanska the underperformance of hedge funds in the QE period. 23 - NEOS Server: State-of-the-art Solvers for Numerical Optimization

27 - Simulation Analysis of Chaotic Storage Policies in Amazon Class Fulfillment Centers Sanchoy Das, New Jersey Institute of Technology, University Heights, Newark, NJ, 07102, United States of America, das@njit.edu, Sevilay Onal 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. 28 - Spatial-temporal Coverage Evaluation Methodology for Multi-satellite Embedded Sensors 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, Diogo Maciel Almeida, Maria Jose Pinto 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. 29 - Stochastic Optimization Methods for Nurse Staffing in Inpatient Settings Parisa Eimanzadeh, Wichita State University, 1845 Fairmount Street, Wichita, KS, 67260, United States of America, pxeimanzadeh@wichita.edu, Ehsan Salari 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. 30 - A Systems Dynamics Model for Flight Test Knowledge Management 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 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. 31 - A Supply Chain Network Equilibrium Model with Carbon Capacity and Social Responsibility Xiaoling Fu, School of Economics and Management, Southeast University, Si Pai Lou 2#, Nanjing, 210096, China, fufei1980@163.com, Lin Zhu, Xiangxiang Huang, Xiaogan Jiang 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. 32 - How to Catch a Black Swan David Gallop, Professor Of Program Management, Defense Acquisition University, 6735 Surbiton Dr, Clifton, VA, 20124, United States of America, davegallop@aol.com 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. 33 - Cost-effectiveness Analysis of Immunosuppression Therapy in Primary Deceased Donor Renal Transplantation Zahra Gharibi, SMU, 5507 Stonehenge Drive, Richardson, TX, 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. 75082, United States of America, zgharibi@smu.edu, Mehmet Ayvaci, Bekir Tanriover, Michael Hahsler

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