Volume 30, Issue 2 (IJIEPR 2019)                   IJIEPR 2019, 30(2): 207-223 | Back to browse issues page

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Asadi-Gangraj E, Bozorgnezhad F, Paydar M M. A Simultaneous Worker Assignment and Scheduling Problem to Minimize Makespan in Flexible Flow Shop via Metaheuristic Approaches. IJIEPR 2019; 30 (2) :207-223
URL: http://ijiepr.iust.ac.ir/article-1-860-en.html
A Simultaneous Worker Assignment and Scheduling Problem to Minimize Makespan in Flexible Flow Shop via Metaheuristic Approaches
Ebrahim Asadi-Gangraj 1, Fatemeh Bozorgnezhad2 , Mohammad Mahdi Paydar2
1- Babol Noshirvani University of Technology , e.asadi@nit.ac.ir
2- Babol Noshirvani University of Technology
Abstract:   (3614 Views)
In many real scheduling situations, it is necessary to deal with the worker assignment and job scheduling together. However, in traditional scheduling problems, only the machine is assumed to be a constraint and there isn’t any constraint about workers. This assumption could be due to the lower cost of workers compared to machines or the complexity of workers' assignment problems. This research proposes a flexible flow shop scheduling problem with two simultaneous issues: finding the best worker assignment, and solving the corresponding scheduling problem. We present a mathematical model that extends flexible flow shop scheduling problem to admit the worker assignment. Due to the NP-hardness of the research problem, two approximation approaches based on particle swarm optimization, named PSO and SPSO, are applied to minimize the makespan. The experimental results show that the proposed algorithms can efficiently minimize the makespan but the SPSO generates better solutions especially for large-size problems.
Keywords: flexible flow shop, worker assignment, MILP model, particle swarm optimization, simulated annealing
Full-Text [PDF 973 kb]   (1475 Downloads)    
Type of Study: Research | Subject: Material Managment
Received: 2018/11/5 | Accepted: 2019/05/8 | Published: 2019/06/22
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