Abstract
Over the past three decades extensive search have been done on pure m-machine flow shop problems. Many researchers faced the Flow Shop Scheduling Problem (FSSP) by means of well-known heuristics which, are successfully used for certain instances of the problem providing a single acceptable solution. Current trends involve distinct evolutionary computation approaches.
This work shows an implementation of diverse evolutionary approaches on a set of flow shop scheduling instances, including latest approaches using a multirecombination feature, Multiple Crossovers per Couple (MCPC), and partial replacement of the population when possible stagnation is detected. A discussion on implementation details, analysis and a comparison of evolutionary and conventional approaches to the problem are shown.
The Research Group is supported by the Universidad Nacional de San Luis and the ANPCYT (National Agency to Promote Science and Technology). http://www-pr.unsl.edu.ar/proyecto338403/home_page.html
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© 2000 Springer-Verlag Berlin Heidelberg
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Esquivel, S.C., Zuppa, F., Gallard, R.H. (2000). Multirecombinated Evolutionary Algorithms for the Flow Shop Scheduling Problem. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_26
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DOI: https://doi.org/10.1007/3-540-45356-3_26
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