An Improved Gaming Particle Swarm Algorithm Based the Rules of Flexible Job Shop Scheduling

Abstract

Job shop scheduling problem (JSP) has been proved a NP-Hard problem. As the extension of JSP, flexible job shop scheduling problem (FJSP) is more complex combinatorial optimization problem than JSP, and is closer to the real process of production than JSP. FJSP is one of classic problems of intelligent manufacturing and its study owns an important value of theory and the significance of directing actual production. The searching mechanisms of tradition particle swarm optimization algorithm (PSO) are improved based on the scheduling theories and criteria under the help of the gaming results among different objectives. After testing standard benchmarks and comparing the results with other results obtained with other improved PSOs, the improved gaming PSO is proved effectively to minimize the maximum complete time of FJSP.