Genetic algorithms with different representation schemes for complex hybrid flexible flow line problems Online publication date: Sat, 08-May-2010
by Thijs Urlings, Ruben Ruiz, Funda Sivrikaya Serifoglu
International Journal of Metaheuristics (IJMHEUR), Vol. 1, No. 1, 2010
Abstract: This paper introduces some advanced genetic algorithms for a complex hybrid flexible flow line problem with a makespan objective that was recently formulated. General precedence constraints among jobs are taken into account, as are machine release dates, time lags and sequence dependent set-up times; both anticipatory and non-anticipatory. This combination of constraints captures many real world industrial problems; among those is the ceramic tile production that served as our inspiration. The introduced algorithms employ solution representation schemes with different degrees of directness. Several new machine assignment rules are introduced and implemented in some proposed genetic algorithms. The different genetic algorithms are compared among each other and to some heuristics as well. The results indicate that simple solution representation schemes result in the best performance, even for complex scheduling problems and that the genetic algorithms lead to a better solution quality than all tested heuristics.
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