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Fattahi, Parviz, Samouei, Parvaneh. (1395). A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers. نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 9(20), 9-18. doi: 10.22094/joie.2016.246
Parviz Fattahi; Parvaneh Samouei. "A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers". نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 9, 20, 1395, 9-18. doi: 10.22094/joie.2016.246
Fattahi, Parviz, Samouei, Parvaneh. (1395). 'A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers', نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 9(20), pp. 9-18. doi: 10.22094/joie.2016.246
Fattahi, Parviz, Samouei, Parvaneh. A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers. نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 1395; 9(20): 9-18. doi: 10.22094/joie.2016.246

A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers

Journal of Optimization in Industrial Engineering
مقاله 2، دوره 9، شماره 20، آذر 2016، صفحه 9-18    اصل مقاله (1.79 M)
نوع مقاله: Original Manuscript
شناسه دیجیتال (DOI): 10.22094/joie.2016.246
نویسندگان
Parviz Fattahi* ؛ Parvaneh Samouei
Bu-Ali Sina University
چکیده
This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm. This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm

تازه های تحقیق
  • A multi-objective particle swarm optimization algorithm for worker assignment and mixed-model assembly line balancing problem is developed.
  • It is assumed that task times depend on the worker’s skill level.
  • The efficiency of the proposed algorithm is compared with multi-objective simulated annealing algorithm 
کلیدواژه‌ها
Mixed-model assembly line balancing؛ Multi-Objective Optimization؛ different skilled workers؛ particle swarm optimization؛ simulated annealing
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