Research on shipboard material scheduling optimization based on improved genetic algorithm

Jinghua Li; Wenhao Huang; Boxin Yang; Qinghua Zhou

doi:10.1117/12.2640942

20 September 2022 Research on shipboard material scheduling optimization based on improved genetic algorithm

Jinghua Li, Wenhao Huang, Boxin Yang, Qinghua Zhou

Proceedings Volume 12261, International Conference on Mechanical Design and Simulation (MDS 2022); 122613T (2022) https://doi.org/10.1117/12.2640942
Event: Second International Conference on Mechanical Design and Simulation (MDS 2022), 2022, Wuhan, China

Abstract

In order to improve the loading optimization efficiency of the pipe fitting pallet assembly in the ship pipe processing workshop, the loading problem of the pipe processing workshop was studied for the low efficiency of pipe pallet transportation in the traditional workshop, and a mathematical model of loading with the goal of maximizing space utilization was established. According to the characteristics of pipe fittings and fusion of heuristic search methods, an improved genetic algorithm is proposed to solve the optimization problem of ship pipe fittings, and the effectiveness and practicability of the algorithm are verified through experiments.

Citation Download Citation

Jinghua Li, Wenhao Huang, Boxin Yang, and Qinghua Zhou "Research on shipboard material scheduling optimization based on improved genetic algorithm", Proc. SPIE 12261, International Conference on Mechanical Design and Simulation (MDS 2022), 122613T (20 September 2022); https://doi.org/10.1117/12.2640942

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