Abstract
The Job Shop Scheduling Problem is a paradigm of Constraint Satisfaction Problems that has interested to researchers over the last decades. In this paper we confront this problem by means of a Genetic Algorithm that is hybridized with a local search method. The Genetic Algorithm searches over the space of active schedules, whereas the local search does it over the space of semi-active ones. We report results from an experimental study over a set of selected problem instances showing that this combination of search spaces is better than restricting both algorithms to search over the same space. Furthermore we compare with the well-known Genetic Algorithms proposed by D. Mattfeld and the Branch and Bound procedure proposed by P. Brucker and obtain competitive results.
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González, M.A., Vela, C.R., Varela, R. (2006). Scheduling with Memetic Algorithms over the Spaces of Semi-active and Active Schedules. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_40
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DOI: https://doi.org/10.1007/11785231_40
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