Fuzzy flexible assembly job shop scheduling under dual resource constraints considering assembly sequence variation

In this study, a fuzzy flexible assembly job shop scheduling considering assembly sequence variation under dual resource constraints (FFAJSS-ASVDRC) is proposed to optimize the part processing sequence and assembly sequence simultaneously under dual resource constraints, considering the uncertainty of operation time. By analyzing the problem in FFAJSS-ASVDRC, a mathematical model is established aiming to minimize the total production completion time, total inventory time and total cost. Furthermore, in order to assign operation, machine and worker reasonably, a three-layer segmented hybrid chromosome encoding structure is designed. Meanwhile, a Q-Learning based genetic algorithm (QLGA) is proposed to realize the adaptive adjustment of the crossover range of chromosomes to improve the quality of the obtained non-dominated solutions. In the case study, the effectiveness, superiority and robustness of QLGA is verified in solving the FFAJSS-ASVDRC problem.