In order to meet the needs of warehouse cooperative scheduling and the problems of slow convergence and prematurity of existing genetic algorithms, we propose a warehouse genetic scheduling algorithm based on leader selection operator. Firstly, the population was divided into male subgroups and female subgroups, and the optimal solution was selected as the female leader and the male leader respectively in two subgroups. Secondly, female leader and male subgroup, male leader and female subgroup are staggered to form a waiting crossover sequence. Finally, an example simulation of the storage genetic scheduling algorithm is designed. The simulation results show that the leader selection operator proposed in this paper is superior to the roulette selection operator and the traversal selection operator in terms of convergence speed and global optimization ability, and improves the efficiency of coordinated storage scheduling.


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    Titel :

    Storage Genetic Scheduling Algorithm Based on Leader Selection Operator


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Yi (Herausgeber:in) / Martinsen, Kristian (Herausgeber:in) / Yu, Tao (Herausgeber:in) / Wang, Kesheng (Herausgeber:in) / Zhang, Tianshu (Autor:in) / Gao, Xiue (Autor:in) / Wang, Kesheng (Autor:in) / Chen, Shifeng (Autor:in)

    Kongress:

    International Workshop of Advanced Manufacturing and Automation ; 2020 ; Zhanjiang, China October 12, 2020 - October 13, 2020



    Erscheinungsdatum :

    23.01.2021


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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