Informs Annual Meeting 2017

SB54

INFORMS Houston – 2017

SB54

2 - Risk-sensitive Cooperative Games for Human-Machine Systems Matthew Stern, Columbia University, New York, NY, United States, mns2141@columbia.edu Autonomous systems can substantially enhance a human’s efficiency and effectiveness in complex environments. Machines, however, are often unable to observe the preferences of the humans that they serve. Though the human’s and machine’s objectives are aligned, asymmetric information, along with heterogeneous sensitivities to risk by the human and machine, make their joint optimization process a game with strategic interactions. We propose a framework based on risk-sensitive dynamic games to model applications including self- driving taxis and robo-financial advising. 3 - Strategic Dynamic Pricing with Network Effects Ali Makhdoumi, MIT, 77 Massachusetts Ave. , 32D-640, Cambridge, MA, 02139, United States, makhdoum@mit.edu, Azarakhsh Malekian, Asu Ozdaglar We study the optimal pricing policy of a committed monopolist selling durable goods in a dynamic pricing game with multiple rounds. Customers are forward- looking and experience a (positive) network effect. The monopolist announces and commits to a price sequence and strategic buyers decide on when (if ever) to buy the good in a perfect Bayesian equilibrium. We explicitly find the optimal pricing policy and show that it is linearly increasing in time, where the slope of the price path is described by a single network measure: sum of the entries of the inverse of network effects matrix. 4 - Reducing Bias in Event Time Simulation VIA Measure Changes Alexander Shkolnik, University of California-Berkeley, Berkeley, CA, 94720, United States, ads2@berkeley.edu Stochastic point process models of event timing are common in many areas, including finance, insurance and reliability. Monte Carlo simulation is often used to perform computations in these models. The standard sampling algorithm, which is based on a time-scaling argument, is widely applicable but generates biased simulation estimators. This article develops a measure change technique for reducing the bias and accelerating the algorithm. We prove the existence of a broad class of measure changes that yields martingales of independent interest. The result ensures that our algorithm has the same scope as the standard time- scaling scheme. Numerical results illustrate our approach. 362C Applications of Location Analysis Sponsored: Location Analysis Sponsored Session Chair: Sibel Alumur Alev, University of Waterloo, University of Waterloo, Waterloo, ON, N2L 3G1, Canada, sibel.alumur@uwaterloo.ca 1 - Risk Aware Capacitated Facility Location Problems Stefan Nickel, Karlsruhe Insitute of Technology, Institute for In this talk we present a new exact algorithmic framework for solving multi-stage stochastic mixed 0-1 problems based on a branch-and-bound approach. The approach can be applied to multi-stage problems with mixed-integer variables and uncertainty in each time stage.We describe the underlying scenario tree with a unique set of indices that enables an easy reformulation of the deterministic equivalent model.Computational results are presented for risk-aware capacitated facility location problems with multiple stages as well as uncertain demand and capacities. The results show that the presented method leads to the optimal solution for all considered instances with a good performance. 2 - A Mathematical Model for Point-to-point Based Airline Network Design Problems Mihiro Sasaki, Nanzan University, 18 Yamazato, Showa, Nagoya, 466-8673, Japan, mihiro@nanzan-u.ac.jp, Takehiro Furuta We consider an airline network design model for passenger transportation based on point-to-point services in which hubs are not necessarily required. We formulate the problem as an integer programming problem and propose a dynamic programming heuristic method to solve large-sized problems. We report some analytical results from passengers’ perspectives. SB56 Operations Research, Karlsruhe, 76131, Germany, stefan.nickel@kit.edu, Tanya Gonser, Iris Heckmann, Francisco Saldanha-da-Gama

362A Models for the Management of Agriculture Industry Invited: Agricultural Analytics Invited Session Chair: Foad Iravani, University of Washington, Foster School of Business, Seattle, WA, 98195, United States, firavani@uw.edu 1 - Transfer Price and Yield Risk-sharing Contracts for Cotton Supply Chains Guang Xiao, Hong Kong Polytechnic University, Hong Kong, guang.xiao@polyu.edu.hk, Panos Kouvelis, Li Jian Motivated by the practices from cotton supply chains, we propose a stylized model to study the contracting interactions among a ginner and its farmers with the presence of crop diversification and side selling. We propose a yield risk- sharing contract to better align the yield and price risks in the supply chain. 2 - Farmland Allocation with Crop Rotation Benefits Javad Nasiry, Hong Kong University of Science and Technology- HKUST, Hong Kong Uni. of Sci. and Tech., ISOM.Dept.,, Lee Shau Kee Business Building, Room 4079, Hong Kong, nasiry@ust.hk, Onur Boyabatli, Yangfang Zhou We examine a farmer’s decision on how to allocate the available farmland between two crops when the crops have rotation benefits across growing seasons. The allocation decision is subject to revenue uncertainty in commodity markets. We characterize the optimal dynamic allocation policy. We then calibrate our model using the data from the United States Department of Agriculture to represent a typical Iowa farmer growing corn and soybean. 3 - Pulses Supply Chains in India: Issues and Solutions Bin Hu, UNC Chapel Hill, McColl Building CB3490, Kenan-Flagler Business School, Chapel Hill, NC, 27599, United States, bin_hu@unc.edu, Liying Mu, Srinagesh Gavirneni Pulses are a vital source of plant-based protein for the large number of vegetarians in India. Unpredictable domestic yields and limited import availability in times of need have recently caused crises for India. Many solutions (e.g., export restrictions, minimum support prices, long-term contracts) have been proposed to address the issues inherent to pulses supply chains and there is widespread debate on which to pursue. We evaluate the role of long-term contracts in resolving these supply chain problems and specifically evaluate the impact of contract timing, uncertainty, budget constraints, and salvage value. 4 - An Analysis of Price vs. Revenue Protection Government Subsidies in the Agriculture Industry Foad Iravani, University of Washington, Foster School of Business, ISOM.Department, Box 353226, Seattle, WA, 98195-3226, United States, firavani@uw.edu, Saed Alizamir, Hamed Mamani We develop models to analyze the effects of government subsidy programs in the agriculture industry on consumers, farmers, and the government. We provide insights about the impacts of crop and market characteristics on the relative performance of subsidies. 362B Statistics and Probability in Finance Sponsored: Financial Services Sponsored Session Chair: Agostino Capponi, Columbia University, Columbia University, New York, NY, 10027, United States, ac3827@columbia.edu 1 - The Optional Sampling Theorem Philip Ernst, Rice University, Houston, TX, United States, philip.ernst@rice.edu Suppose you have one unit of stock, currently worth 1, which you must sell before time $T$. The Optional Sampling Theorem tells us that whatever stopping time we choose to sell, the expected discounted value we get when we sell will be 1. Suppose however that we are able to see $a$ units of time into the future, and base our stopping rule on that; we should be able to do better than expected value 1. But how much better can we do? And how would we exploit the additional information? The optimal solution to this problem will never be found, but in this paper we establish remarkably close bounds on the value of the problem, and we derive a fairly simple exercise rule that manages to extract most of the value of foresight. SB55

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