2016 INFORMS Annual Meeting Program

WD72

INFORMS Nashville – 2016

2 - Better Bounds On Convergence Rates For First-order Methods In Sequential Games Christian Kroer, Carnegie Mellon University, Computer Science Department, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United States, ckroer@cs.cmu.edu, Fatma Kılınç-Karzan, Kevin Waugh, Tuomas W Sandholm First-order methods, are known to be very effective in solving large-scale two- player zero-sum extensive-form games. The convergence rates of these methods depend heavily on an associated distance-generating function. By introducing a new weighting scheme for the dilated entropy function, we develop the first distance-generating function for the strategy spaces of sequential games that has no dependence on the branching factor of the player. This significantly improves the convergence rate of several first-order methods. Numerical experiments further support the effectiveness of our new weighting scheme by demonstrating better practical convergence rates. 3 - Formulation Of A Continuous Equilibrium Mapping And A Simplicial Path-following Method For Approximating Proper Equilibria Yabin Sun, City University of Hong Kong, Nam Shan Office-705, Hong Kong, yabinsun-c@my.cityu.edu.hk, Yin Chen, Chuangyin Dang This paper formulates a continuous equilibrium mapping for a specifically defined perturbed game that deforms with an extra variable. As a result of this formulation, we develop a simplicial path-following method for approximating a proper equilibrium. The method follows a simplicial path that starts from any given totally mixed strategy profile and leads to a proper equilibrium. Numerical results further confirms the effectiveness of the method. 4 - Price Of Anarchy In Bayesian Congestion Games Manxi Wu, Massachusetts Institute of Technology, 235 Albany Street, 3112B, Cambridge, MA, 02139, United States, manxiwu@mit.edu, Saurabh Amin We study a new model of congestion games to understand the effects of asymmetric information on the equilibrium costs of individual players and the social cost. We present a full characterization of the Bayesian Wardrop Equilibrium (BWE) of the game by exploiting the properties of a weighted potential function. We compare the equilibrium cost in any BWE to the socially optimal costs under incomplete and perfect information structures. Our main result estimates the contribution to the price of anarchy (PoA) of the game due to two factors: selfish routing and information heterogeneity. Chair: Richard Titus, PhD Candidate at Penn State, Adjunct Lehigh Univ, The Pennsylvania State University, 310 Leonhard Building, University Park, PA, 16802, United States, rjt4@lehigh.edu 1 - Can A Buyer Benefit From Bounded Rationality? Sha Luo, North Carolina State University, 4335 Avent Ferry Road, Apt 3, Raleigh, NC, 27606, United States, sluo3@ncsu.edu, Russell Edward King, Shu-Cherng Fang Abstract: Bounded rationality takes into account that human decision makers are prone to biases and mistakes. General wisdom suggests that people fail to reap the highest level of benefits when they are not perfectly rational. In this study, we consider a supplier pricing game when the retailer is not a perfect optimizer. The decision model of bounded rationality is derived from the classical logit model. We apply the concept of Nash equilibrium to predict the rational outcome of the pricing game when two suppliers submit their wholesale prices simultaneously. It is found that bounded rationality can be advantageous to the buyer when her bounded rationality level is moderate. 2 - Using Point-of-sale Data To Improve Shelf Replenishment Performance Suzanne de Treville, University of Lausanne, Anthropôle 3073, Lausanne-Dorigny, CH1015, Switzerland, suzanne.detreville@unil.ch, Valérie Chavez-Demoulin, Joerg S Hofstetter Shelf replenishment for a retail chain is done once daily. Point-of-sale data lets us estimate the value of a second replenishment opportunity. We begin from a standard newsvendor approach with flexible second-replenishment capacity made available, and show that flexible capacity will often outperform capacity allocated at the level of single stock-keeping units. We define a “Demand at Risk” measure similar to Value at Risk in quantitative finance that captures the highest demand that might be reasonably encountered, and use machine-learning techniques to identify data features of the data that may signal increases in the Demand at Risk, warranting priority replenishment. WD72 Bass- Omni Supply Chain, Decision I Contributed Session

3 - A Structurally Enhanced Fuzzy Inference System Partner Selection Technique In Forming Virtual Enterprise Shahrzad Nikghadam, PhD Student, Middle East Technical University, 425, graduate studies dorm,METU, Cankaya, Ankara, 06800, Turkey, shahrzad.nikghadam@metu.edu.tr, Hakki Ozgur Unver, Ahmet Murat Ozbayoglu, Sadik Engin Kilic In this study we considered a partner selection problem of Virtual Enterprise in forming consortiums based on customer preferences. Previously, we have presented a Fuzzy Inference System (FIS) based methodology for the problem. Though, in this study, an enhanced form of the previous model is presented by editing the fuzzy rules and their reasoning structure. New rules are established by asking fewer questions from customer, yet the computational results show that it still gives the reasonable decisions by having less detailed information about the customer. 4 - Supplier Selection Models With Product Life Cycle Considerations Richard Titus, PhD Candidate at Penn State, Adjunct Lehigh Univ, The Pennsylvania State University, 310 Leonhard Building, University Park, PA, 16802, United States, rjt4@lehigh.edu This research examines the global supplier selection process and includes supplier attributes, determined by an empirical case study and product life cycle considerations. The empirical study examines the relationship of key supplier attributes to quality and delivery performance. Goal programming methodologies, including Preemptive, Non-preemptive, Chebycheff’s Min/Max and Fuzzy GP, are used to solve the multi-objective supplier selection problem for the four product life cycle phases. An illustrative example and an industrial case study are included in the testing of the supplier selection models. WD73 Legends A- Omni Operations Management VIII Contributed Session Chair: Donald Paul Warsing, North Carolina State University, College of Management, Campus Box 7229, Raleigh, NC, 27695-7229, United States, don_warsing@ncsu.edu 1 - Leveraging Suppliers To Calibrate Product Specification Sha Liao, University of the Fraser Valley, Vancouver, BC, Canada, sha.liao@ufv.ca, Hao Zhang, Yimin Wang We examine a two-period game between an Original Equipment Manufacturer (OEM) and his supplier during new product development. The supplier may detect specification problems during production. We first prove that it is strictly better for the OEM to design the contract so that the supplier will voluntarily point out specification problems. We then characterize the optimal contract for the OEM. 2 - Private Label Encroachment And Supply Chain Information Sharing Xue Li, Tsinghua University, Beijing, China, xueli@mit.edu, Yanchong Zheng, Jian Chen Our paper investigates the retailer’s private label encroachment strategy and its implications for the national brand manufacturer and the retailer in the environment where the national brand manufacturer may have private product intrinsic information. We consider information sharing via cheap talk in this setting, investigate the effects of private label encroachment on credible information sharing and show that the private label strategically introduced by the retailer may also benefit the national brand manufacturer. 3 - Supply Chain To Product Matching And Firm Performance Donald Paul Warsing, North Carolina State University, College of Management, Campus Box 7229, Raleigh, NC, 27695-7229, United States, don_warsing@ncsu.edu, Mohamed Desoky, Russell Edward King, Mark Walker We present an empirical analysis of Fisher’s (1997) conceptual model of supply chain-to-product matching. We use longitudinal COMPUSTAT data across several industries and develop proxies to measure Fisher’s characterizations of products (functional vs. innovative) and supply chains (efficient vs. responsive), and we find a strong, positive relationship between the strength of a firm’s market performance and the strength of the match between its product and supply chain characteristics.

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