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.
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Mirghorbani, S.M., Rabbani, M., Tavakkoli-Moghaddam, R., Rahimi-Vahed, A.R. (2007). A Multi-Objective Particle Swarm for a Mixed-Model Assembly Line Sequencing. In: Waldmann, KH., Stocker, U.M. (eds) Operations Research Proceedings 2006. Operations Research Proceedings, vol 2006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69995-8_30
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DOI: https://doi.org/10.1007/978-3-540-69995-8_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69994-1
Online ISBN: 978-3-540-69995-8
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