Dual-resource flexible job shop scheduling considering dual-layer learning effects
LU Chao
YU Fei
GONG Wen-yin
YUAN Zhi-hua
Abstract：In the era of Industry 5.0,human-centred intelligent manufacturing has become a hot research topic.For the dual-resource flexible job shop scheduling problem,studies have considered the learning effect of workers,but have not yet addressed the impact of the dual-layer learning effect of workers on jobs and machines on production efficiency.For this reason,this paper proposes for the first time a two-resource flexible job shop scheduling problem considering the dual-layer learning effect of workers,and constructs a mathematical model with maximum completion time as the optimisation objective.To solve the problem,an improved Memetic algorithm is proposed,and the main improvements include:De-signing a three-layer encoding that meets the problem characteristics,proposing an active scheduling decoding strategy to improve the solution quality,developing a population initialisation strategy to enhance the diversity,and designing a fusion of cross-variance updating and variable-neighbourhood searching strategies to improve the ability of global exploration and local optimisation.Finally,the effectiveness of the algorithm and model is verified by comparison experiments.
Keywords：flexible job shop scheduling problemdual-layer learning effects of workersMemetic algorithm
Publication Date：2025-11-30
Online Publishing Date：2025-12-29(First online date of this platform, not the publication date of the document)
Pages：14( 2296-2309 )