Informs Annual Meeting 2017

MC38

INFORMS Houston – 2017

2 - Coordinating a Dual-channel Supply Chain with a Risk-averse Retailer under Deferred Payment Bo Li, College of Management and Economics at Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, 300072, China, libo0410@tju.edu.cn The study considers a dual-channel supply chain with a risk-averse retailer under a deferred payment contract. We design a benchmark without deferred payment to compare the equilibrium solutions. We find that if the retailer is moderately risk-averse and the unit production cost is large, the profits of the manufacturer and the entire supply chain will decrease as she tends to be risk-neutral, and vice versa. In addition, whether the two agents benefit from the deferred payment depends on two key parameters (unit production cost and risk-averse attitude). Finally, a mixed contract that combines revenue sharing and deferred payment is introduced to coordinate the dual-channel supply chain. 3 - A Responsive Pricing Retailer Sourcing from Competing Suppliers Facing Disruption Tao Li, Santa Clara University, 2730 Park Ave Apt 3, Santa Clara, CA, 95050, United States, tli1@scu.edu, Suresh P.Sethi, Xi Shan We study a problem of a retailer who orders from two competing strategic suppliers subject to independent or correlated disruptions and responds by setting the retail price upon delivery. We model it as a Stackelberg-Nash game with the suppliers as the leaders and the retailer as the follower. We identify a scenario in which an increase in the reliability of a supplier may, counter to our intuition, hurt him. In the literature without responsive-pricing, the retailer’s profit increases and a supplier’s profit decreases in the disruption correlation, whereas with responsive-pricing, the retailer’s profit increases and a supplier’s profit may not decrease in the disruption correlation. 4 - Pricing of New Product Technologies in Supply Chains and Technology Markets Ayhan Aydin, George Mason University, 4400 University Drive, Enterprise Hall, Fairfax, VA, 22030, United States, aaydin2@gmu.edu Upstream firms can market their technology to downstream tiers either by licensing the use of the technology or through a product carrying the advanced technology. We compare the levels of technology transfer under three different price tariffs - only fixed tariff, only variable tariff, and two-part tariff - and under two methods of marketing on the level of technology transferred. 352C Parametric LCP and Multiobjective Optimization Sponsored: Multiple Criteria Decision Making Sponsored Session Chair: Margaret M Wiecek, Clemson University, Clemson, SC, 29634-1907, United States, wmalgor@clemson.edu 1 - A Two-Phase Algorithmfor the Multi-Parametric Linear Complementarity Problem with Sufficient Matrices and Parameters in General Locations Nathan Adelgren, Edinboro University of PA, 159 Ross Hall, Edinboro, PA, 16444, United States, nadelgren@edinboro.edu In this talk we present a new two-phase procedure for solving the multiparametric Linear Complementarity Problem (mpLCP) with sufficient matrices. As the variant of mpLCP considered in this talk was previously unsolved, we first consider the theoretical properties of this problem which allow it to be solved. We then present the solution procedure and explore its use on an example. Finally, we present the results of some preliminary computational experiments. 2 - Multiobjective Quadratic Programming: State of the Art and Application to Portfolio Optimization Pubudu Jayasekara Merenchige, Clemson University, Clemson, SC, 29634, United States, pwijesi@clemson.edu, Margaret M. Wiecek, Nathan Adelgren We review algorithms for computing efficient solutions to multiobjective quadratic programs (MOQPs) and analyze their applicability to the portfolio selection problem. We compare the algorithms with respect to the type of MOQPs they can handle. The type is determined by the number of quadratic criteria and the properties of the feasible set. 3 - On the Robustness Gap in Uncertain Multiobjective Optimization Margaret M.Wiecek, Clemson University, Mathematical Sciences Dept, Clemson, SC, 29634-1907, United States, wmalgor@clemson.edu, Corinna Krüger, Anita Schöbel We propose a definition of robustness gap in uncertain multiobjective optimization. Under convexity assumptions and using of the weighted-sum scalarization, we derive upper and lower bounds for the gap that are easier to calculate than the gap itself. We also specify conditions under which the gap is zero. MC38

4 - A Cost to Coverage Ratio Based Heuristic Algorithm for the Multiobjective Set Covering Problem Lakmali Weerasena, University of Tennessee Chattanooga, 9629 Shooting Star Circle, Chattanooga, TN, 37379, United States, lakmali-weerasena@utc.edu The multiobjective set covering problem (MOSCP), a NP-hard combinatorial optimization problem, has received limited attention in the literature from the perspective of approximating its Pareto set. We present a two-phase heuristic algorithm to approximate the Pareto set of the MOSCP. Computational experiments on instances with two, three and four-objective set covering problems are conducted to analyze the performance of the algorithm. 352D Smart Services and Service Systems Sponsored: Service Science Sponsored Session Chair: Robin Qiu, Pennsylvania State University, Malvern, PA, 19355, United States, robinqiu@psu.edu 1 - Research on the Quality Promotion System of Logistics Service Zuqing Huang, PhD, China Jiliang University, Hangzhou, 310018, China, hzq1210@163.com With the rapid development of e-commerce, the logistics industry has been got the rapid development. But the quality of logistics service is unsatisfied. From the perspective of the quality of logistics service, this paper constructed the index system of logistics service and provided a method to evaluate the quality of logistics service. 2 - A Patient-centric Approach to Mitigating Alzheimer’s Disease Progression Robin Qiu, Pennsylvania State University, 30 E. Swedesford Road, Malvern, PA, 19355, United States, robinqiu@psu.edu In 2016, about 5.4 million Americans were diagnosed with Alzheimer’s disease (AD). The project was to develop a predictive model to classify a patient into normal, mild, and moderate, and severe AD stages. Based on the patient’s cognition evaluation, we aim to develop a cheap, convenient, and accurate self- diagnostic tool. More importantly, actionable factors that could slow down the disease’s progression are determined. Hence, this study would be able to facilitate developing a platform to guide an individual in making the necessary lifestyle choices, ultimately resulting in retaining or rejuvenating the brain’s cognitive ability of the individual. 3 - Identification of Critical Quality Dimensions for Continuance Intention in mHealth Services: A Case Study of Onecare Service Ki-Hun Kim, Pohang University of Science and Technology, 77 Cheongam-Ro Nam-Gu, Engineering Building 4-316, Pohang, Gyeongbuk, 790-784, Korea, Republic of, kh_kim@postech.ac.kr, Kwang-Jae Kim, Dae-Ho Lee, Min-Geun Kim Mobile health (mHealth) services provide health-related support through mobile devices. Onecare is an mHealth service to support health behavior monitoring of college students by utilizing daily behavior data collected through activity trackers and smartphones. This study aims to identify the quality dimensions that are crucial for users’ intention to continue the use of Onecare based on the survey responses of 191 Onecare users. This study would serve as a basis for planning mHealth service improvement to enhance users’ continuance intention. 4 - Directed Disease Networks in Support of Multiple-disease Risk Prediction Modeling Tingyan Wang, Ph.D candidate, Tsinghua University, Beijing, 100084, China, wangty14@mails.tsinghua.edu.cn, Robin Qiu, Ming Yu In this study, we propose a novel framework that combines directed disease network and collaborative filtering techniques for multiple disease risk prediction modeling. Firstly, a directed disease network considering temporal information was built on grouped diseases. Then based on this network, we explore different disease risk score computing approaches. We validate the proposed methods with real-world datasets. The results demonstrate the potential value of the proposed modeling framework, e.g. a reference for medical experts to provide patients healthcare guidance, or a tool helps individuals design a better healthcare plan over time. MC39

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