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作者：Blanchet, Jose; Gallego, Guillermo; Goyal, Vineet
作者单位：Columbia University; Hong Kong University of Science & Technology
摘要：Assortment planning is an important problem that arises in many industries such as retailing and airlines. One of the key challenges in an assortment planning problem is to identify the right model for the substitution behavior of customers from the data. Error in model selection can lead to highly suboptimal decisions. In this paper, we consider a Markov chain based choice model and show that it provides a simultaneous approximation for all random utility based discrete choice models includin...
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作者：Stenius, Olof; Karaarslan, Ayse Gonul; Marklund, Johan; de Kok, A. G.
作者单位：Lund University; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; Eindhoven University of Technology
摘要：Sustainable and efficient management of a distribution system requires coordination between transportation planning and inventory control decisions. In this context, we consider a one warehouse multi-retailer inventory system with a time-based shipment consolidation policy at the warehouse. This means that there are fixed costs associated with each shipment, and retailer orders are consolidated and shipped periodically to groups of retailers sharing the same delivery routes. Customer demand is...
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作者：Lejeune, Miguel A.; Margot, Francois
作者单位：George Washington University; Carnegie Mellon University
摘要：We propose a new and systematic reformulation and algorithmic approach to solve a complex class of stochastic programming problems involving a joint chance constraint with random technology matrix and stochastic quadratic inequalities. The method is general enough to apply to nonconvex as well as nonseparable quadratic terms. We derive two new reformulations and give sufficient conditions under which the reformulated problem is equivalent. The second reformulation provides a much sparser repre...
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作者：Xu, Huan; Caramanis, Constantine; Mannor, Shie
作者单位：National University of Singapore; University of Texas System; University of Texas Austin; Technion Israel Institute of Technology
摘要：We consider optimization problems whose parameters are known only approximately, based on noisy samples. In large-scale applications, the number of samples one can collect is typically of the same order of (or even less than) the dimensionality of the problem. This so-called high-dimensional statistical regime has been the object of intense recent research in machine learning and statistics, primarily due to phenomena inherent to this regime, such as the fact that the noise one sees here often...
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作者：Bertsimas, Dimitris; Dunning, Iain
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
摘要：We present a new partition-and-bound method for multistage adaptive mixed-integer optimization (AMIO) problems that extends previous work on finite adaptability. The approach analyzes the optimal solution to a static (nonadaptive) version of an AMIO problem to gain insight into which regions of the uncertainty set are restricting the objective function value. We use this information to construct partitions in the uncertainty set, leading to a finitely adaptable formulation of the problem. We u...
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作者：Kim, Michael Jong
作者单位：University of Toronto
摘要：This paper is concerned with optimal maintenance decision making in the presence of model misspecification. Specifically, we are interested in the situation where the decision maker fears that a nominal Bayesian model may be miss-specified or unrealistic, and would like to find policies that work well even when the underlying model is flawed. To this end, we formulate a robust dynamic optimization model for condition-based maintenance in which the decision maker explicitly accounts for distrus...
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作者：Bensoussan, Alain; Jang, Bong-Gyu; Park, Seyoung
作者单位：University of Texas System; University of Texas Dallas; City University of Hong Kong; Pohang University of Science & Technology (POSTECH); National University of Singapore
摘要：We develop a new approach for solving the optimal retirement problem for an individual with an unhedgeable income risk. The income risk stems from a forced unemployment event, which occurs as an exponentially distributed random shock. The optimal retirement problem is to determine an individual's optimal consumption and investment behaviors and optimal retirement time simultaneously. We introduce a new convex-duality approach for reformulating the original retirement problem and provide an ite...
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作者：Gopalakrishnan, Ragavendran; Doroudi, Sherwin; Ward, Amy R.; Wierman, Adam
作者单位：Carnegie Mellon University; University of Southern California; California Institute of Technology
摘要：Traditionally, research focusing on the design of routing and staffing policies for service systems has modeled servers as having fixed (possibly heterogeneous) service rates. However, service systems are generally staffed by people. Furthermore, people respond to workload incentives; that is, how hard a person works can depend both on how much work there is and how the work is divided between the people responsible for it. In a service system, the routing and staffing policies control such wo...
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作者：Kocuk, Burak; Jeon, Hyemin; Dey, Santanu S.; Linderoth, Jeff; Luedtke, James; Sun, Xu Andy
作者单位：University System of Georgia; Georgia Institute of Technology; University of California System; University of California Berkeley; University of Wisconsin System; University of Wisconsin Madison
摘要：It is well known that optimizing network topology by switching on and off transmission lines improves the efficiency of power delivery in electrical networks. In fact, the USA Energy Policy Act of 2005 (Section 1223) states that the United States should encourage, as appropriate, the deployment of advanced transmission technologies including optimized transmission line configurations. As such, many authors have studied the problem of determining an optimal set of transmission lines to switch o...
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作者：Dahleh, Munther A.; Tahbaz-Salehi, Alireza; Tsitsiklis, John N.; Zoumpoulis, Spyros I.
