A Conic Integer Programming Approach to Stochastic Joint Location-Inventory Problems
成果类型：
Article
署名作者：
Atamtuerk, Alper; Berenguer, Gemma; Shen, Zuo-Jun (Max)
署名单位：
University of California System; University of California Berkeley
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1110.1037
发表日期：
2012
页码：
366-381
关键词：
摘要：
We study several joint facility location and inventory management problems with stochastic retailer demand. In particular, we consider cases with uncapacitated facilities, capacitated facilities, correlated retailer demand, stochastic lead times, and multicommodities. We show how to formulate these problems as conic quadratic mixed-integer problems. Valid inequalities, including extended polymatroid and extended cover cuts, are added to strengthen the formulations and improve the computational results. Compared to the existing modeling and solution methods, the new conic integer programming approach not only provides a more general modeling framework but also leads to fast solution times in general.