Informs Annual Meeting 2017

TC21

INFORMS Houston – 2017

TC19

TC20

342A Ops-Finance: Risk, Strategy, and Service Sponsored: Manufacturing & Service Oper Mgmt, iFORM Sponsored Session Chair: Mike Pinedo, mpinedo@stern.nyu.edu Co-Chair: Yuqian Xu, New York University, New York, NY, 10012, United States, yxu@stern.nyu.edu 1 - The Effectiveness of Supplier Buy Back Finance: Evidence from the Chinese Automobile Industry Weiming Zhu, IESE Business School, Avenida Pearson 21, Barcelona, 08034, Spain, zhuwm923@gmail.com, Tunay Tunca Facing a budget-constrained buyer, a novel approach for large suppliers is adopting buy-back financing schemes to relieve their downstream partners and reduce channel costs. Through counterfactual analysis, we analyze the efficiency of these financing schemes. We find that such contract agreements can improve channel efficiency over traditional financing methods. 2 - Default Risk Premia and a Non Linear Asset Pricing Model The value of an equity investment can be framed as an embedded call option on a firm’s assets. The embedded call option creates a non-linear relationship between stock returns and underlying risk factors. In addition, losses given default create discontinuities in the value of these options that are differentially determined for firms with distinct characteristics, such as size and value. We introduce a non- linear equity pricing model that includes these aspects of potential default consequences and seems to explain and predict individual stock returns. 3 - Merchant Energy Trading in a Network Selvaprabu Nadarajah, College of Business, University of Illinois at Chicago, 601 South Morgan Street, UH 2406, Chicago, IL, 60607, United States, selvan@uic.edu, Nicola Secomandi Motivated by practice, we formulate a merchant trading energy in a network of storage and transport assets as a Markov decision process with uncertain energy prices. We develop tractable approximate dynamic programming methods to obtain operating policies and bounds, also highlighting the importance of joint storage and transport optimization. 4 - Operational Risk Management: Preventative v.s. Corrective Controls Yuqian Xu, University of Illinois at Urbana-Champaign, Champaign, IL, United States, yxu@stern.nyu.edu, Lingjiong Zhu, Mike Pinedo In this paper, we consider a stochastic control framework with a jump process to analyze the impact of large shocks caused by operational risk events on a financial firm’s value process. We study capital investments in the infrastructure of a financial firm that aims at mitigating the impact of operational risk events. We characterize the analytical solutions of optimal investment strategies as a function of the rm’s growth rate, the jump process parameters, and a loss reduction function. Our modeling framework, combining a typical operational risk process with stochastic control, suggests a future research direction in operations management and operational risk management. 5 - Sourcing from Suppliers with Financial Constraints and Performance Risk Yi Zhang, Illinois Institute of Technology and Accenture Management Consulting, Chicago, IL, United States, marco.y.zhang@chicagobooth.edu, John R. Birge

342B Telecommunications Contributed Session Chair: Kagan Gokbayrak, Bilkent University, Ankara, Turkey, kgokbayr@bilkent.edu.tr 1 - Local Search Methods for Link Scheduling Problem of Wireless Mesh Networks Kagan Gokbayrak, Professor, Bilkent University, Ankara, 06800, Turkey, kgokbayr@bilkent.edu.tr, Yucel Naz Yetimoglu We aim to increase the average connection speed of a wireless mesh communication network, whose transmissions are scheduled to occur at different time slots, by decreasing the average queueing delay. Under steady state conditions, the average queueing delay is linearly proportional to the average queue size, so we search for the link schedule that minimizes the time-average of the sum of queue lengths over all nodes. We formulate a Mixed Integer Linear Programming problem and solve this NP-hard problem by the Simulated Annealing and the k-change local search methods. We also conduct computational experiments on several example networks to demonstrate the performances of these methods. 2 - A Branch and Cut Algorithm to Design LDPC Codes with out Industrial Engineering, Department, Istanbul, 34342, Turkey, banu.kabakulak@boun.edu.tr, Z. Caner Ta kın, Ali Emre Pusane In a digital communication system, information is sent from one place to another over a noisy communication channel using binary symbols (bits). Original information is encoded by adding redundant bits, which are then used by low- density parity-check (LDPC) codes to detect and correct the errors. Error correction capability of an LDPC code is severely degraded due to small cycles in its bipartite graph representation (Tanner graph). We introduce an integer programming formulation for generating Tanner graphs which do not include cycles smaller than a given size. We propose a branch-and-cut algorithm for its solution. 3 - Device Caching in Mobile Networks: Modeling and Optimization D I.YUAN, Professor, Uppsala University, Department of Information Tech, Uppsala, 751 05, Sweden, di.yuan@it.uu.se, Tao Deng, Ghafour Ahani, Pingzhi Fan Caching files at user devices in mobile networks is gaining research interest in the field of telecommunications. We consider a cost-optimal caching problem for device-to-device communications. In this presentation, we provide recent results on modeling and optimization of the cost-optimal caching problem. Specifically, we discuss a bounding approach using integer programming, to approximate the cost function that models mobility using stochastic distribution, and derive a low- complexity algorithm. Performance evaluation of the proposed schemes are presented and discussed. Small Cycles in Communication Systems Banu Kabakulak, PhD, Bogazici University,

TC21

342C Optimization for Disaster Response Invited: InvitedNatural Hazard Planning Invited Session

Jing Wu, City University of Hong Kong, Department of Management Sciences, Rm 7-233, Lau Ming Wai Academic Building, Hong Kong, Hong Kong, jingwu49@cityu.edu.hk, Christopher S.Tang, S. Alex Yang

Chair: Elise Miller-Hooks, George Mason University, miller@gmu.edu Co-Chair: Vadim Sokolov, George Mason University, SEOR Dept., MS4A6, 4400 University Drive, Fairfax, VA, 22030, United States, vsokolov@gmu.edu 1 - The Information Collecting Vehicle Routing Problem: Stochastic Optimization for Emergency Storm Response Lina Al-Kanj, Princeton University, Olden Street, Sherrerd Hall, Office 115, Princeton, NJ, 08542, United States, lina.kanj@gmail.com In this talk, a new policy is presented that routes a utility truck to restore outages in the power grid using trouble calls and the truck’s route as mechanisms for collecting information to create beliefs about outages. This means that routing decisions change our belief about the network, creating the first stochastic vehicle routing problem that explicitly models information collection. First, the problem is formulated as a sequential stochastic optimization. Then, a stochastic lookahead policy is presented that uses Monte Carlo tree search to produce a practical policy that is asymptotically optimal. Simulation results show that the developed policy has a close-to-optimal performance.

Two innovative financing schemes have emerged in recent years that were intended to enable suppliers to obtain financing for production, Purchase Order Financing (POF) and Buyer Direct Financing (BDF). In this talk, we use a game- theoretical model to examine the relative efficiency of these two schemes. We find that both POF and BDF yield the same payoff under symmetric information, and However, information asymmetry only lowers the efficiency of POF when the supplier’s asset level is sufficiently low.

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