Abstract
Problems involving assembly lines optimization have been target of many researchers due to its relevance in practical applications. The Assembly Line Balancing Problem is directly related to the productivity of assembly lines. However, its NP-Hard nature makes the problem solution becomes non-trivial for exact procedures, which makes room for metaheuristic approaches. In this work, we applied six recent variations of the Fish School Search algorithm in the solution of the Simple assembly Line Balancing Problem Type 1 and compared either solution quality and convergence speed against the results obtained by other three metaheuristic procedures. The different approaches were compared through statistical tests and the results give an indication of which procedure is most suitable for this class of combinatorial optimization problems.
Keywords
- Metaheuristics
- Fish school search
- Assembly line balancing problem
- Genetic algorithms
- Ant colony optimization
- Particle swarm optimization
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The authors thank to CAPES (Coordination for the Improvement of Higher-Education Personnel), Brazil, for the partial financial support for this paper.
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de Albuquerque, I.M.C., Filho, J.B.M., Neto, F.B.L., Silva, A.M.O. (2017). Fish School Search Variations and Other Metaheuristics in the Solution of Assembly Line Balancing Problems. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_35
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DOI: https://doi.org/10.1007/978-3-319-53480-0_35
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