2015 Informs Annual Meeting

SD77

INFORMS Philadelphia – 2015

3 - Conditional Probability of Correct Selection for Ranking and Selection Procedures Dave Goldsman, Professor, Georgia Tech, School of ISyE, Georgia Tech, Atlanta, GA, 30332, United States of America, sman@gatech.edu, Joshua Mcdonald Ranking and selection (R&S) procedures seek to select the best of a number of competing populations, subject to a guarantee on the achieved probability of correct selection (PCS). In the usual formulations of R&S problems, the guaranteed PCS is specified a priori. We instead study the conditional PCS after sampling has concluded - which may be substantially different than the a priori version. In particular, we show how to compute or estimate the conditional PCS given the observed scenario. 4 - Efficient Optimization via Multi-fidelity Simulation Jie Xu, George Mason University, 4400 University Dr., MS 4A6, Engr Bldg, Rm 2100, Fairfax, VA, 22030, United States of America, jxu13@gmu.edu, Si Zhang, Edward Huang, Loo Hay Lee, Nurcin Celik, Chun-hung Chen To efficiently solve optimization problems involving time-consuming high-fidelity simulations, we propose a new multi-fidelity optimization framework known as MOTOS. MOTOS uses low-fidelity simulations to broadly explore the solution space and focuses high-fidelity simulations on promising solutions. MOTOS integrates low- and high-fidelity simulations in an efficient and rigorous manner and has been shown to lead to significant computational savings. Chair: Chun Hung Chiu, Associate Professor, Associate Professor, Sun Yat-sen University, Business School, Sun Yat-sen University, No 135, Xingang West Rd., Guangzhou GD 510275, China, zhaojx5@mail.sysu.edu.cn 1 - Public Versus Private Quality Disclosure of Counterfeit Goods Laura Wagner, Zaragoza Logistics Center, Calle Bari, Zaragoza, Spain, laurawa@mit.edu, Mustafa Cagri Görböz, Mahmut Parlar Some manufacturers have been accused for withholding information on counterfeit incidences, while others have proactively warned. We analyse this situation in a supply chain setting. In particular we are interested in manufacturer’s willingness to disclose the quality of the potentially counterfeit good, intermediary’s purchasing decision in response to the disclosure strategy and consumers’ responses to such warnings. 2 - Mean Variance Analysis for Supply Chain Contract Jinfeng Yue, Professor, Middle Tennessee State University and Shanghai University of Finance and Economics, Department of Management and Marketing, Murfreesboro, TN, 37132, United States of America, jinfeng.yue@mtsu.edu This research studies the supply chain coordination by mean-variance analysis. When only the mean and variance information is available, the coordination conditions are obtained for wholesale price contract. The maximum number of retailers can also be determined. For general cases, the conditions to select the retailers are also obtained. Finally, an optimal designed wholesale price contract can coordinate the supply chain and split the total profit by any designed level. 3 - Economic Contracts Improving the Efficiency of Cotton Supply Chains Jian Li, Associate Professor, Northeatern Illinois University, 5500 N. St. Louis Ave, Chicago, IL, 60625, United States of America, jli@neiu.edu, Panos Kouvelis We study the use of economic contracts to improve the efficiency of a stylized cotton supply chain structure of a ginner and a farmer. The benchmark is a standard transfer price contract that reflects the current practice on which a minimum price is imposed from the government. We show that the minimum transfer price is not necessarily effective. An incentive contract is proposed. Numerical studies show that the incentive contract achieves a win-win improvement. SD77 77-Room 300, CC Supply Chain Management IV Contributed Session

4 - Supply Chain Performance Assessment and Supplier and Component Importance Identification Dong Michelle Li, Assistant Professor of Supply Chain Management, Department of Management & Marketing, Arkansas State University, Jonesboro, AR, 72467, United States of America, dli@astate.edu, Anna Nagurney We develop a multitiered competitive supply chain network game theory model with firms and associated potential suppliers. All decision-makers seek to maximize their profits. The supply chain network performance measures, which assess efficiency, are constructed for the full supply chain and the individual firm levels. The identification and ranking of the importance of suppliers as well as the components of suppliers with respect to the full supply chain or individual firm are also proposed. 5 - Channel Coordination under Information Asymmetry by Target Sales Rebate Quantity Discount Contracts Chun Hung Chiu, Associate Professor, Sun Yat-sen University, Business School, Sun Yat-sen University, No 135, Xingang West Rd., Guangzhou, GD, 510275, China, zhaojx5@mail.sysu.edu.cn, Jian Li, T.c.e. Cheng, Tsan Ming Choi We study a target sales rebate quantity discount (TSR-QD) contract in a single- manufacturer and multi-retailer supply chain. The manufacturer is risk-neutral. Retailers are mean-variance seekers with different target profits which are unknown to the manufacturer. We explore how a Menu of TSR-QD Contracts (MTQ) can be applied to enhance the benefit of the manufacturer and the supply chain’s efficiency. SD78 78-Room 301, CC Supply Chain Risk Management II Contributed Session Chair: Saravanan Kuppusamy, Assistant Professor, Quinnipiac University, 275 Mt Carmel Ave, Hamden, CT, 06518, United States of America, saravanan.kuppusamy@quinnipiac.edu 1 - A Fair Optimization of Expected Cost and Expected Service under Disruption Risks Tadeusz Sawik, Professor And Chair, AGH University of Science & Technology, Al. Mickiewicza 30, Krakow, 30059, Poland, ghsawik@cyf-kr.edu.pl A new decision-making problem of equitably efficient optimization of cost and service level in a supply chain under local and regional disruption risks is presented. The problem is formulated as a mixed integer program with the ordered weighted averaging aggregation of the two conflicting objective functions. Computational examples and some managerial insights are reported. 2 - Risk Assessment in a Large Retail Supply Chain Burak Kazaz, Associate Professor, Syracuse University, 721 University Avenue, Syracuse, NY, 13244, United States of America, bkazaz@syr.edu, Mert Hakan Hekimoglu, John Park This study develops a new risk exposure index for various infrastructures in a large retail supply chain. It identifies detrimental disruptions, considers operational and financial metrics with excess capacity at distribution centers and fulfillment centers that can serve as backup facilities. It provides risk levels at all facilities. 3 - Risk Modeling in Food Supply Chain, Insights Saravanan Kuppusamy, Assistant Professor, Quinnipiac University, 275 Mt Carmel Ave, Hamden, CT, 06518, United States of America, saravanan.kuppusamy@quinnipiac.edu, Mario Norbis, Iddrisu Awudu Issues related to food supply chain are becoming increasingly critical for the business and policy makers alike. We propose a food supply chain research framework that consider issues related to location, legislation, corporate responsibility, collaboration, risk measures, food safety and security measures. In addition to managerial insights and implications, we discuss the challenges and opportunities in food supply chains. 4 - Decision Model for Prioritization of Reverse Supply Chain Risks Dr Jitender Madaan, Professor, Indian Institute of Technology Delhi, Room No 606 DMS, VK Bhawan, Hauz Khas, New Delhi, 110016, India, jmadaan@dms.iitd.ac.in This paper presents a flexible, generalized decision model that integrates and prioritize high-level and detailed RSC design decisions that incorporates risks.

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