An Improved Gaming Particle Swarm Optimization Algorithm for Flexible Job-shop Scheduling Problems

Abstract:

The research on flexible job-shop scheduling problems （FJSP） can help the production in practical to meet the ascending demands of personalization and customization from special customers. On the basis of a full study of scheduling criteria on FJSP， the paper proposes a gaming particle swarm optimization algorithm gaming PSO） with novel encoding and decoding schemes. In comparison with the traditional PSO， the communication mechanism of the proposed PSO is improved by a gaming solution set， which takes advantages of the contradictions among the scheduling criteria. Finally，based on a test of the standard benchmarks and a comparative study of the test results with those by other improved PSOs， the proposed gaming PSO proves to be effective in minimizing the maximum completion time of FJSP.