A Multi-Objective Particle Swarm for a Mixed-Model Assembly Line Sequencing

Seyed Mohammed Mirghorbani (), Masoud Rabbani, Reza Tavakkoli-Moghaddam and Alireza R. Rahimi-Vahed
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Seyed Mohammed Mirghorbani: University of Tehran
Masoud Rabbani: University of Tehran
Reza Tavakkoli-Moghaddam: University of Tehran
Alireza R. Rahimi-Vahed: University of Tehran

A chapter in Operations Research Proceedings 2006, 2007, pp 181-186 from Springer

Abstract: Abstract Mixed-model assembly line sequencing is one of the most important strategic problems in the field of production management. In this paper, three goals are considered for minimization; That is, total utility work, total production rate variation, and total setup cost. A hybrid multi-objective algorithm based on Particle Swarm Optimization (PSO) and Tabu Search (TS) is devised to solve the problem. The algorithm is then compared with three prominent multi-objective Genetic Algorithms and the results show the superiority of the proposed algorithm.

Keywords: Particle Swarm Optimization; Ideal Point; Real Encode; Total Setup Cost; Elite Tabu Search (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-3-540-69995-8_30

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