Performance Evaluation of a Parameter-Free Genetic Algorithm for Job-Shop Scheduling Problems
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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].
[1] Hidefumi Sawai,et al. Parameter-Free Genetic Algorithm Inspired by "Disparity Theory of Evolution" , 1998, PPSN.
[2] Sheik Meeran,et al. Deterministic job-shop scheduling: Past, present and future , 1999, Eur. J. Oper. Res..
[3] Ken-ichi Tokoro,et al. Real-Coded Parameter-Free Genetic Algorithm for Job-Shop Scheduling Problems , 2002, PPSN.