Prioritization via Stochastic Optimization

• 成果类型: Article
• 署名作者: Koc, Ali; Morton, David P.
• 署名单位: International Business Machines (IBM); IBM USA; University of Texas System; University of Texas Austin
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2013.1865
• 发表日期: 2015
• 页码: 586-603
• 关键词: priority lists; activity-selection problem; Stochastic Programming; cutting planes

摘要

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.