Abstract
Assembly line balancing problems are concerned with the distribution of work required to assemble a product in mass or series production among a set of work stations on an assembly line. The specific problem considered here is known as the time and space constrained simple assembly line balancing problem. Among several possible objectives we consider the one of minimizing the number of necessary work stations. This problem is denoted by TSALBP-1 in the literature. For tackling this problem we propose an extended version of our Beam-ACO approach published in [3]. Beam-ACO algorithms are hybrid techniques that result from combining ant colony optimization with beam search. The experimental results show that our algorithm is able to find 128 new best solutions in 269 possible cases.
This work was supported by grants TIN-2005-08818-C04-01 and DPI2004-03475 of the Spanish government, and by the Ramón y Cajal program of the Spanish Ministry of Science and Technology of which Christian Blum is a research fellow. Moreover, we acknowledge Nissan Spain and the UPC Nissan Chair for partially funding this work.
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Blum, C., Bautista, J., Pereira, J. (2008). An Extended Beam-ACO Approach to the Time and Space Constrained Simple Assembly Line Balancing Problem. In: van Hemert, J., Cotta, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2008. Lecture Notes in Computer Science, vol 4972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78604-7_8
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DOI: https://doi.org/10.1007/978-3-540-78604-7_8
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