Mixed-integer simulation optimization for multi-echelon inventory problems with lost sales

作     者：Tsai, Shing Chih Wang, Honggang Hung, Li Hsuan 

作者机构：National Cheng Kung University Tainan City Taiwan California State Polytechnic University-Pomona PomonaCA United States 

出 版 物：《Journal of the Operational Research Society》 (J.Oper.Res.Soc.)

年 卷 期：2023年第74卷第11期

页      面：2312-2326页

核心收录：

学科分类：0711[理学-系统科学] 12[管理学] 0202[经济学-应用经济学] 1202[管理学-工商管理] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0811[工学-控制科学与工程] 0701[理学-数学] 

主　　题：Approximation algorithms 

摘      要：We propose a mixed-integer simulation optimization framework for solving multi-echelon inventory problems with lost sales. We want to seek optimal settings of the order-up-to levels and the review intervals for warehouse and retailers. The aim is to minimize the total expected costs including the inventory holding cost, the ordering cost and the penalty cost. The proposed optimization method represents a complementary combination of ranking-and-selection procedures and stochastic-approximation algorithms for both integer-valued and real-valued variables. We provide a proof for the finite-time statistical validity of the developed algorithm. We also discuss the convergence conditions for the asymptotic optimality of our algorithm. The algorithmic performance is examined with experiments under different parameter settings and stopping conditions. During the experiments, our algorithm performs favorably in comparison to the popular Arena optimization tool, OptQuest. © Operational Research Society 2022.