Formulation and Methods for a Class of Two-stage Flow-shop Scheduling Problem with the Batch Processor

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@InProceedings{Wang:2020:CASE,

• author = "Runsen Wang and Yilan Shen and Weihao Wang and Leyuan Shi",
• title = "Formulation and Methods for a Class of Two-stage Flow-shop Scheduling Problem with the Batch Processor",
• booktitle = "2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)",
• year = "2020",
• pages = "728--733",
• abstract = "Motivated by the heat-treating process in a launch vehicles manufacturing plant, we study a two-stage scheduling problem with limited waiting time where the first stage is a batch processor and the second stage is a discrete machine. A mixed-integer programming model is developed and two lower bounds are derived to measure the performance of proposed algorithms. An efficient heuristic together with worst-case analysis is also proposed. Genetic Programming approaches are applied to the flow-shop scheduling problem. Numerical results demonstrate that the proposed algorithms perform better than other meta-heuristics in different production scenarios.",
• keywords = "genetic algorithms, genetic programming, Batch production systems, Job shop scheduling, Processor scheduling, Heating systems, Numerical models, Heuristic algorithms",
• DOI = "doi:10.1109/CASE48305.2020.9216748",
• ISSN = "2161-8089",
• month = aug,
• notes = "Also known as \cite{9216748}",

}

Genetic Programming entries for Runsen Wang Yilan Shen Weihao Wang Leyuan Shi

Citations