Mengyi Zhang, A. Matta, A. Alfieri, Giulia Pedrielli
{"title":"A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem","authors":"Mengyi Zhang, A. Matta, A. Alfieri, Giulia Pedrielli","doi":"10.1109/COASE.2017.8256247","DOIUrl":null,"url":null,"abstract":"The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2017.8256247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.