2015 Informs Annual Meeting

TC63

INFORMS Philadelphia – 2015

2 - Designing a Reliable Bio-fuel Supply Chain Network Considering Link Failure Probabilities Linkan Bian, Assistant Professor, Mississippi State University, 260 McCain Building, Starkville, MS, 39762, United States of America, bian@ise.msstate.edu, Sushil Poudel, Mohammad Marufuzzaman This study presents a pre-disaster planning model that seeks to strengthen the multi-modal facilities links for a bio-fuel supply chain system under limited budget availability. The failure probability of the links are estimated using a spatial-statistical model. We developed a combinatorial Benders decomposition algorithm to solve this challenging NP-hard problem. 3 - Managing Congestion in a Multi-modal Facility Location Problem under Uncertainty

5 - Progressive Modeling: Towards a New Complex Systems Optimization Paradigm Mohamed Ismail, Assistant Professor, University of Regina, 3737 Wascana Parkway, Regina, SK, S4S0A2, Canada, mohamed.ismail@uregina.ca Progressive Modeling (PM) is a multidisciplinary forward-looking modeling approach that finds pragmatic solutions for many complex and large-scale industrial problems. Many related applications will presented to demonstrate the principles and the techniques adopted in this paradigm. The new modeling paradigm is expected to have many engineering applications and influence many disciplines such as systems optimization, Operations management, and system of systems engineering. TC64 64-Room 113A, CC Panel Discussion: Analytics and Decision Analysis Sponsor: Decision Analysis Sponsored Session Chair: Jeffrey Keisler, University of Massachusetts Boston, Moderator:Jeffrey Keisler, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, MA, 02125, United States of America, Jeff.Keisler@umb.edu, Panelists: Jeff Vales, Casey Lichtendahl, John Turner, Don Kleinmuntz, Max Henrion Huge increases in data availability and computing power have transformed quantitative fields and led to a proliferation of tools for analytics. Panelists will discuss how can DA strengthen analytics broadly defined, and how can analytics strengthen DA. TC65 65-Room 113B, CC Joint Session DAS/MAS:Game Theory, Decision Analysis, and Homeland Security, Part B Sponsor: Decision Analysis Sponsored Session Chair: Jun Zhuang, University at Buffalo, SUNY, 317 Bell Hall, Buffalo, NY, 14221, United States of America, jzhuang@buffalo.edu 1 - Modeling A Multi-target Attacker-defender Resource Allocation Game Considering Risk Preferences Jing Zhang, University at Buffalo, SUNY, 338 Bell Hall, Buffalo, NY, 14221, United States of America, jzhang42@buffalo.edu, Jun Zhuang, Victor Richmond Jose Although evidence has been found that people often demonstrate risk preference when faced with risky decisions, the literature mostly assumed that adversaries are risk-neutral. This paper models a sequential attacker-defender game where the defender allocates defensive resources to multiple targets while considering the risk preferences of both the defender and attacker. We study the cases when the attacker could be either non-strategic, or strategic. 2 - Game Theoretic Analysis of Secret and Reliable Communication Melike Baykal-görsoy, Rutgers, The State University of New Jersey, 96 Frelinghuysen Road, CoRE Building, Room 201, Piscataway, NJ, 08854, United States of America, gursoy@rci.rutgers.edu Secret and reliable communication presents a challenge involving a double dilemma for a user and an adversary. To get insight into this problem, we present two simple stochastic games. Explicit solutions are found. In addition, we show that under some conditions, incorporating in the transmission protocol a time slot dealing just with the detection of malicious threats can improve the secrecy and reliability of the communication without extra transmission delay. 3 - Optimal Cost-sharing in General Resource Selection Games Konstantinos Kollias, Stanford University, 474 Gates Building, 353 Serra Mall, Stanford, CA, 94305, United States of America, kkollias@stanford.edu, Tim Roughgarden, Vasilis Gkatzelis Resource selection games provide a model for a diverse collection of applications where a set of resources is matched to a set of demands. In reality, demands are often selfish and congestion on the resources results in negative externalities for their users. We consider a policy maker that can set a priori rules to minimize the inefficiencies induced by selfish behavior and we characterize the control methods that minimize the worst-case inefficiency of equilibria. 100 Morrissey Boulevard, Boston, MA, 02125, United States of America, Jeff.Keisler@umb.edu 1 - Analytics and Decision Analysis

Mohammad Marufuzzaman, Mississippi State University, Industrial & Systems Engineering, Starkville, MS, 39762, United States of America, mm2006@msstate.edu

This paper presents a mathematical model that studies the impacts of the congestion effect in a multi-modal facility location design problem under feedstock supply uncertainty. The model is solved using a hybrid algorithm that integrates constraint generation, sample average approximation, progressive hedging and rolling horizon algorithm.

TC63 63-Room 112B, CC Operations Management I Contributed Session

Chair: Mohammed Darwish, Associate Professor, Kuwait University, Industrial and Management Systems Eng., P.O. Box 5969, Safat, 13060, Kuwait, m.darwish@ku.edu.kw 1 - Probabilistic Estimation of the Inventory Shortage Cost Feng Xu, Georgia Southwestern State University, 800 GSW State University Drive, School of Business Administration, Americus, GA, 31709, United States of America, feng.xu@gsw.edu Due to the difficulty in calculating the loss of goodwill, in estimating the shortage cost practitioners and researchers often assume a fixed penalty cost or switch to assigning a specific customer service level. This paper proposes probabilistic measurements of the shortage cost, based on mathematical relationship between the cost and the shortage amount. The derived closed-form estimates of the expected shortage cost can then be applied to determining the optimal inventory control policy. 2 - Optimal Staffing with Endogenous Goals Buket Avci, Singapore Management University, 50 Stamford Road, Singapore, 248196, Singapore, buketavci@smu.edu.sg We investigate the optimal staffing level decision of a firm, when employee performance is indirectly affected by staffing levels through workload. In the spirit of Prospect Theory, we posit that goals act as reference points, and there is an asymmetry between under and over-performance relative to a goal. We solve the corresponding principal-agent model in a queueing context and characterize conditions when endogenous goals are relevant for staffing decisions. 3 - Quality Management Theory Development via Meta-analysis Xianghui Peng, University of North Texas, 1307 West Highland Street, College of Business, Denton, TX, 76201, United States of America, xianghui.peng@unt.edu, Victor Prybutok, Robert Pavur A meta-analysis is conducted on the empirical studies in quality management (QM). The results allow evaluation of the relationship strength among QM practices, performance, and content factors. The longitudinal evaluation in this study investigates how relationships and content factors in the post-2005 period compare with the pre-2005 period. 4 - Determination of the Maximum Worth of Auctioned Lots using Acceptance Sampling Method Mohammed Darwish, Associate Professor, Kuwait University, Industrial and Management Systems Eng., P.O. Box 5969, Safat, 13060, Kuwait, m.darwish@ku.edu.kw, Fawaz Abdulmalek In recent years, auction becomes an important method of buying and selling different items around the world. The most common type of auctions that is found in practice is the English Auction where a bidder inspects the auctioned lot by taking a sample and based on the number of defective items found in the sample, he or she takes a critical decision regarding the maximum worth of the auctioned lot. We show how the maximum worth of an auctioned lot can be determined using acceptance sampling.

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