Multi-dual decomposition solution for risk-averse facility location problem

作     者：Yu, Guodong Zhang, Jie 

作者机构：Shandong Univ Sch Management Jinan Shandong Peoples R China Virginia Tech Grad Dept Ind & Syst Engn Blacksburg VA USA 

出 版 物：《TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW》 (Transp. Res. Part E Logist. Transp. Rev.)

年 卷 期：2018年第116卷

页      面：70-89页

核心收录：

学科分类：0201[经济学-理论经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0814[工学-土木工程] 0823[工学-交通运输工程] 

基　　金：Shandong Province Natural Science Foundation [ZR2018QG001] Fundamental Research Funds of Shandong University Ministry of Education (MOE) Academic Research Fund (AcRF) Tier 1 [R-266-000-087-112] 

主　　题：Facility location Risk-averse Conditional value-at-risk Mixed-integer nonlinear programming Duality gap Multi-dual decomposition 

摘      要：We consider the risk-averse uncapacitated facility location problem under stochastic disruptions. By the Conditional-value-at-risk, we control the risks at each individual customer, while previous works usually control the entire networks. We show that our model provides more reliable solutions than previous ones. The resulting formulation is a mixed-integer nonlinear programming. In response, we develop a multi-dual decomposition algorithm based on the augmented Lagrangian and classic penalty function. A class of decomposed unconstrained subproblems are then solved by an iterative approach not relying on Lagrange multipliers and differentiability. Our experiments show that the algorithm performs well even for some larger problems.