Prioritization via Stochastic Optimization

Ali Koç () and David P. Morton ()
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Ali Koç: Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598
David P. Morton: Graduate Program in Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, Texas 78712

Management Science, 2015, vol. 61, issue 3, 586-603

Abstract: We take a novel approach to decision problems involving binary activity-selection decisions competing for scarce resources. The literature approaches such problems by forming an optimal portfolio of activities. However, often practitioners instead form a rank-ordered list of activities and select those with the highest priority. We account for both viewpoints. We rank activities considering both the uncertainty in the problem parameters and the optimal portfolio that will be obtained once the uncertainty is revealed. We use stochastic integer programming as a modeling framework, and we apply our approach to a facility location problem and a multidimensional knapsack problem. We develop two sets of cutting planes to improve computation.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1865 . This paper was accepted by Dimitris Bertsimas, optimization.

Keywords: priority lists; activity-selection problem; stochastic programming; cutting planes (search for similar items in EconPapers)
Date: 2015
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