Research on green flexible job-shop scheduling considering dual-resource constraints and multiple-speed
WANG Yu-fang
ZHANG Dian-qing
HUA Xiao-lin
ZHANG Yi
GE Shi-yu
Abstract：Considering the energy consumption differences caused by different machine speeds in actual production workshops and the production requirements of fine processes,a dual-resource-constrained multi-speed green flexible job-shop scheduling model is constructed,with the optimization objectives of maximizing completion time and total machine energy consumption.A learning bee colony algorithm is proposed to solve the model.Using hybrid initialization to obtain the initial population and improve the evolutionary starting point of the algorithm.After the employment bees complete the search,a new bee species is introduced to learn the genes of excellent honey sources,reduce the randomness of the search and improve the search accuracy.Adaptive optimization of learning probabilities is carried out by using the Q-learning operator to ensure the diversity of nectar sources while enhancing the global search capability of the algorithm.A dynamic neighborhood search strategy is designed for the following-bee stage,and a neighborhood structure based on variable speed and balancing the working hours of workers is incorporated to enhance the local search ability of the following bees.The superiority of the proposed algorithm is verified by comparing different algorithms on the extended standard examples.
Keywords：dual-resource constraintsmulti-speedgreen flexible job-shop schedulingmultiobjective optimizationartificial bee colony algorithmQ-learning
Publication Date：2025-10-30
Online Publishing Date：2025-11-13(First online date of this platform, not the publication date of the document)
Pages：9( 2019-2027 )