A novel feature selection for evolving compact dispatching rules using genetic programming for dynamic job shop scheduling

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@Article{DBLP:journals/ijpr/SalamaKFK22,

• author = "Shady Salama and Toshiya Kaihara and Nobutada Fujii and Daisuke Kokuryo",
• title = "A novel feature selection for evolving compact dispatching rules using genetic programming for dynamic job shop scheduling",
• journal = "International Journal of Production Research",
• volume = "60",
• number = "13",
• pages = "4025--4048",
• year = "2022",
• keywords = "genetic algorithms, genetic programming, Discrete event simulation, dispatching rules, dynamic job shop scheduling, feature selection",
• timestamp = "Sun, 02 Oct 2022 01:00:00 +0200",
• biburl = "https://dblp.org/rec/journals/ijpr/SalamaKFK22.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• URL = "https://doi.org/10.1080/00207543.2022.2053603",
• DOI = "doi:10.1080/00207543.2022.2053603",
• abstract = "...we propose a new representation of the GP rules that abstracts the importance of each terminal. Moreover, an adaptive feature selection mechanism is developed to estimate terminals’ weights from earlier generations in restricting the search space of the current generation. The proposed approach is compared with three GP algorithms from the literature and 30 human-made rules from the literature under different job shop configurations and scheduling objectives, including total weighted tardiness, mean tardiness, and mean flow time. Experimentally obtained results demonstrate that the proposed approach outperforms methods from the literature in generating more interpretable rules in a shorter computational time without sacrificing solution quality.",

}

Genetic Programming entries for Shady Salama Toshiya Kaihara Nobutada Fujii Daisuke Kokuryo

Citations