Many assembly lines related optimization problems have been tackled by researchers in the last decades due to its relevance for the decision makers within manufacturing industry. Many of theses problems, more specifically Assembly Lines Balancing and Sequencing problems, are known to be NP-Hard. Therefore, Computational Intelligence solution approaches have been conceived in order to provide practical use decision making tools. In this work, we proposed a simultaneous solution approach in order to tackle both Balancing and Sequencing problems utilizing an effective meta-heuristic algorithm referred as Fish School Search. Three different test instances were solved with the original and two modified versions of this algorithm and the results were compared with Particle Swarm Optimization Algorithm.
@article{arxiv.1707.06185,
title = {Simultaneously Solving Mixed Model Assembly Line Balancing and Sequencing problems with FSS Algorithm},
author = {Joao Batista Monteiro Filho and Isabela Maria Carneiro de Albuquerque and Fernando Buarque de Lima Neto},
journal= {arXiv preprint arXiv:1707.06185},
year = {2017}
}