Abstract
This paper presents a genetic algorithm specially designed for job shop problems. The algorithm has a simple coding scheme and new crossover and mutation operators. A simple local search scheme is incorporated in the algorithm leading to a combined genetic algorithm(CGA). It is evaluated in three famous Muth and Thompson problems (i.e. MT6×6, MT10×10, MT20×5). The simulation study shows that this algorithm possesses high efficiency and is able to find out the optimal solutions for the job shop problems.
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CITATION STYLE
Cai, L. W., Wu, Q. H., & Yong, Z. Z. (2000). A genetic algorithm with local search for solving job problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1803, pp. 107–116). Springer Verlag. https://doi.org/10.1007/3-540-45561-2_11
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