关键词: 柔性作业车间调度问题, 鸟群算法, 随机黑洞策略, 关键路径

Abstract: The flexible job-shop scheduling problem is one of important constrained optimization issues in production?scheduling field. In this paper, a flexible job-shop scheduling method based on improved bird swarm algorithm with objective of minimum completion time is proposed according to its solution characteristics. To improve the population diversity and accelerate the convergence rate of algorithm, a random black-hole strategy is adopted to the foraging method of the bird flock, and the migration step length of the bird flock is used by self-adapting dynamic adjusting strategy. The domain search of the working procedures on critical path is used to enhance the local search ability of the proposed algorithm. In additional, production and processing data of actual manufacturing enterprises and some benchmark test cases are utilized for simulation experiments. It is shown that the proposed algorithm has advantages in solving accuracy and convergence rate, which is proved to be an effective new approach to solve flexible job-shop scheduling problem.

Key words: flexible job-shop scheduling problem, bird swarm algorithm, random black-hole strategy, critical path