Enhancement of Multiprocessors Job Shop Scheduling with Heterogeneous Workers Using Particle Swarm Optimization

Abstract

To present employees’ job processing time with fuzzy numbers, this study utilizes a stepwise function applied to forming maximum completion time as an independent variable to simulate the real work situations. Given that multiprocessor job shop scheduling is applicable to the actual production scenarios, this study chooses multiprocessor job shop with heterogeneous workers scheduling as the subject. This study oriented to the multiprocessor job shop scheduling takes the heterogeneous workers with related subsidies as the constraining factors and endeavors to seek the best solutions to the problem. Finally, simulated data confirm the effectiveness and robustness of the proposed algorithm. The data test results indicate that PSO is a significant heuristic algorithm for the attempted problems.