Product processing prioritization in hybrid flow shop systems supported on Nash bargaining model and simulation-optimization

• Published in: Expert systems with applications Vol. 180; p. 115066
• Main Authors: Malekpour, Hiva, Hafezalkotob, Ashkan, Khalili-Damghani, Kaveh
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 15.10.2021; Elsevier BV
• Subjects: Bargaining; Customer satisfaction; Discrete event systems; Discrete-event simulation; Game scheduling; Hybrid systems; Job shops; Nash bargaining; Optimization; Simulated annealing; Simulation; Simulation-optimization; Workstations; Simulation-optimization; Game scheduling; Nash bargaining; Discrete-event simulation
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2021.115066

•Proposing a game-based simulation–optimization approach in HFS scheduling.•Using bargaining approach to determine the optimal priority processing rule in HFS.•Using scheduling game in an HFS exposed to the stochastic failure of machinery.•The efficiency of the approach due to the significant reduction of makespan. Dynamic scheduling using real-time data in manufacturing systems enables quick response to unforeseen system events to reduce costs and makespan while increasing customer satisfaction. Since many production systems are multi-product, each product’s customers aim to receive the product in the shortest possible time, thus competing with each other. Extant research neglects to consider not only competition between customers, but also bargaining strategies. In this paper, a hybrid flow shop system with multi-product is regarded. The production system studied is the Alborz Tire Company (Iran), which uses multi-type machines subject to stochastic failure. The objective is to determine the product processing prioritization in workstations, based on the Nash bargaining model, to minimize makespan. To this end, a simulation–optimization approach based on discrete-event simulation and Simulated annealing is employed. The results of the case study show that makespan is reduced significantly for all players.