2016 INFORMS Annual Meeting Program

SD41

INFORMS Nashville – 2016

SD39 207A-MCC Queueing Systems and Approximations Sponsored: Applied Probability Sponsored Session Chair: John Hasenbein, University of Texas-Austin, Austin, TX, United States, jhas@mail.utexas.edu 1 - Optimal Routing To Remote Queues Yunan Liu, NC State University, Raleigh, NC, United States, yliu48@ncsu.edu, Shucangchi He, Yao Yu We develop optimal routing policies for remote queueing systems, in which each arrival, after being routed to join one of several single-server queues in parallel, will experience a pre-arrival delay. Motivated by service systems in which system state (e.g., queue length and waiting time) is available for routing decisions, we intend to use pre-arrival delays to model commute times of arrivals, such as patients’ transportation times before arriving at clinics and data packets’ transmission times to web servers. In order to minimize the delay, we propose a new state-dependent probabilistic routing policy. 2 - Complete Resource Pooling In Open Shop Networks Shuangchi He, National University of Singapore, Singapore, heshuangchi@nus.edu.sg, Gideon Weiss, Hanqin Zhang In an open shop network, each customer needs to go through all stations once, but the order of visiting each station is irrelevant. Can this flexibility in service order give us an edge in reducing customer waiting times? In this paper, we consider an open shop network consisting of two stations. We find routing and sequencing policies that are asymptotically optimal when the open shop network is operated in heavy traffic. We prove that under the obtained scheduling policies, customer waiting times in an open shop network are asymptotically close to the waiting times in a GI/GI/2 queue with the same traffic intensity. 3 - Stein Method And Moderate Deviations For Steady-state Diffusion Approximations Jim Dai, Cornell University, jd694@cornell.edu, Fang Xiao Service levels such as no more 5% of callers have to wait 3 minutes orlonger are common performance measures for many service systems. Iwill use the Erlang-C system to explain how Stein method can be used todevelop moderate deviations bounds for steady-state diffusionapproximations of these performance measures. This is the joint work with Xiao Fang at NUS and Chinese University of Hong Kong. 4 - Optimal Service Rate And Admission Control For A Queue Levent Kocaga, Yeshiva University, kocaga@yu.edu We study the joint service rate and admission control problem for a multi-server service system modeled as a G/M/N+GI queue. We consider the infinite horizon discounted cost criterion as well as the infinite horizon average cost criterion where costs are associated with customer waiting, customer abandonment, and service rate control. Instead of solving the potentially intractable original queueing control problem, we solve an approximating diffusion control problem (DCP) and show that the optimal control is of threshold and feedback type. We utilize the solution to the DCP to construct a control policy for the original queueing control problem. SD40 207B-MCC Supply Chain Mgt Contributed Session Chair: Xinghao Yan, Western University, London, ON, Canada, xyan@ivey.uwo.ca 1 - Simulation And Optimization For Reevaluating Order Fulfillment Plans In An Online Retail Environment Amir Hossein Kalantari, University of Wisconsin Milwaukee, Milwaukee, WI, United States, kalanta2@uwm.edu, Matthew Petering Online retailing has expanded dramatically in recent years and is expected to continue growing in the future. Online retailers typically operate a number of fulfillment centers that are located in different geographical regions. When an order is placed, it must be assigned to one or more fulfillment centers. The decision of choosing which fulfillment centers satisfy which orders is very critical and there is an opportunity for the retailer to significantly reduce shipping costs by making the right decisions. In our research, we use a combination of discrete event simulation and optimization to investigate the effects of different strategies and compare their effectiveness.

2 - The Value Of Aggregated Information Sharing In Supply Chains Vladimir Kovtun, Yeshiva University Syms School of Business, New York, NY, vladimir.kovtun@yu.edu We study a two-stage supply chain where the retailer’s order is the aggregate of two stationary ARMA processes. We determine when there is value to sharing the individual processes and when there is additional value to sharing the shocks. We also determine the supplier’s mean squared forecast error under no sharing, process sharing, and shock sharing. We find instances when process sharing has no value which are not present in earlier literature. 3 - Coordination Of The Supply Chain With Quality Improvement And Customer Returns Xinghao Yan, Western University, London, ON, Canada. Contact: xyan@ivey.uwo.ca We study a supply chain with both quality improvement and customer returns. We analyze the retailer’s incentive for refund price and the supplier’s incentive for quality improvement. We also design coordinating contracts for the supply chain, which is influenced by several factors: contract format, profit negotiation, and first-mover right. SD41 207C-MCC Financial Engineering and Risk Management Sponsored: Financial Services Sponsored Session Chair: Ning Cai, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China, ningcai@ust.hk Co-Chair: Yingda Song, University of Science and Technology of China, Jinzhai Road, Hefei, 230026, China, songyd@ustc.edu.cn 1 - Simulating Risk Measures Steven Kou, National University of Singapore, matsteve@nus.edu.sg Risk measures, such as value-at-risk and expected shortfall, are widely used in risk management. We propose a simple general framework, allowing dependent samples, to compute these risk measures via simulation. The framework consists of two steps: In the C-step, we control the relative error in the simulation by computing the necessary sample size needed for simulation, using a newly derived asymptotic expansion of the relative errors for dependent samples; in the S-step, the risk measures are computed by using sorting algorithms. Numerical experiments indicate that the algorithm is efficient even at the 0.001 quantile level. This is a joint work with Wei Jiang. 2 - Valuation Of Path-dependent Equity And Credit Derivatives Ning Cai, Hong Kong University of Science & Technology, ningcai@ust.hk We study the pricing problems of path-dependent equity and credit derivatives within a general hybrid equity-credit framework, i.e., under generalized jump to default extended exponential Levy models with local volatilities. More precisely, under this general model, we propose a unified approach to pricing various equity derivatives and credit derivatives, including defaultable corporate bonds, European options, barrier options, CDS, and EDS. Numerical results indicate that our pricing methods are accurate, efficient, and easy to implement. This is joint work with Haohong Lin from HKUST. 3 - A Unified Framework For Options Pricing Under Regime Switching Models Yingda Song, University of Science and Technology of China, Hefei, China, songyd@ustc.edu.cn Regime changes are prevalent in the financial markets, yet it is challenging to price options in presence of regime switching. In this talk, we provide a unified framework for pricing options under a wide class of regime switching models. Based on our framework, we study the effects of regime switching on the prices and hedge parameters of various types of options, as well as the yield spread of a structural credit model.

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