Improved simulated annealing algorithm for flexible job shop scheduling problems

Because of computational complexity and a lot of constrained conditions, it is difficult to obtain the optimal solution for the flexible job shop scheduling problem (f-JSP). This paper constructs the f-JSP with the minimum manufacturing period and job delivery time limitation. Inspired by particle swarm algorithm optimization process, we propose an improved simulated annealing algorithm (ISA) for the problem. The ISA improves a single particle of simulated annealing process to co-evolution between particles in the group, and produces a good group by better particle guiding. The combination of SA and GA can effectively improve the global and local search ability. Simulation experiments show that the model is more close to the reality and the proposed algorithm is advanced and the success rate is high.