An Improved Discrete Particle Swarm Optimization Algorithm for a Single Batch-Processing Machine with Non-identical Job Sizes

This paper aims at minimizing the makespan for a single batch-processing machine with non-identical job sizes (NSBM) using discrete particle swarm optimization algorithm (DPSO). PSO is a natural continuous function algorithm and there is some obstacle to solve combinatorial optimization problems. Recently, some hybrid PSO or DPSO have been presented by researchers to solve discrete problems in practical applications but no application to NSBM problems hitherto. DPSO is improved in some operators, adaptive factors and some other details in this paper. The computational simulation results and comparisons show that the DPSO algorithm is competitive for the NSBM problems.