A probabilistic model toward a permutation flowshop scheduling problem with imperfect jobs. Issue 3 (2nd July 2016)

• Record Type: Journal Article
• Authors: Bootaki, Behrang; Paydar, Mohammad Mahdi
• Is Part Of: International journal of management science and engineering management. Volume 11:Issue 3(2016)
• Page Start: 186
• Page End: 193
• Publication Date: 2016-07-02
• Subjects: permutation flowshop scheduling problem -- rework -- makespan; C16 -- C44 -- C61 -- C63 -- M11; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2015.1045048
• Languages: English
• ISSNs: 1750-9661

Abstract

Abstract : This article addresses a permutation flowshop scheduling problem with rework activities. The concept of a reworkable job here means that a job on a machine may need more than one operation to reach a predefined quality level, stochastically. Therefore in this configuration, processing times become random variables with a known probability distribution. The objective function is the minimization of the expected makespan. The solution mechanism is based on using mathematical expectations of processing times in order to find a job sequence by solving a mixed integer mathematical model, then assessing the makespan of the obtained sequence by running several simulated trials and reporting the mean value. In other words, a flowshop scheduling problem with stochastic processing times on machines is considered in this article, and the solution approach merges a mixed integer programming model and simulation. Finally a comprehensive, randomly generated example is presented for verifying the proposed problem. According to the results, the existence of reworkable jobs in a flowshop scheduling problem can change the optimum job sequence when minimization of the makespan is assumed.