Abstract: An improved particle swarm optimization algorithm with global search ability is proposed to minimize the makespan of a single batch-processing machine with non-identical job sizes.The coding method of the algorithm is designed according to the processing of non-identical jobs.The global best solutions are improved using a chaotic scheme to avoid the immature convergence.The simulation results demonstrate that the proposed algorithm outperforms the other algorithm on the run time and the quality of solutions.

Key words: scheduling, batch-processing machine, non-identical job, chaos, particle swarm optimization