Improved Bat Algorithm for Solving Flexible Job-shop Scheduling Problems

On the basis of the analysis and research on bat algorithm, we propose an improved discrete bat algorithm to solve the flexible job-shop scheduling problem. Specifically, we propose a single-integeren coding strategy in order to express the relationship effectively between the process and the particle population. The algorithm redefines the relative operator of the speed and the position of the particle. In order to overcome the shortcomings of the fixed parameters in the basic bat algorithm, we adjust the value of the inertia weight, after which we propose an inertia weight strategy. The experimental data show that the improved algorithm is an effective scheduling algorithm that can effectively solve flexible job-shop scheduling problems.