Abstract
The job-shop scheduling problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Genetic Algorithms (GAs) for solving the JSSP have been proposed, and they perform well compared with other approaches [1].
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References
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Matsui, S., Watanabe, I., Tokoro, Ki. (2003). Performance Evaluation of a Parameter-Free Genetic Algorithm for Job-Shop Scheduling Problems. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_43
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DOI: https://doi.org/10.1007/3-540-45110-2_43
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