Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/157515
Authors: 
Rabbani, Masoud
Montazeri, Mona
Farrokhi-Asl, Hamed
Rafiei, Hamed
Year of Publication: 
2016
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 12 [Year:] 2016 [Pages:] 485-497
Abstract: 
Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.
Subjects: 
Mixed-model assembly lines
U-shaped assembly lines
Learning and training effect
Human-related issues
Multi-objective
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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