强化哈里斯鹰算法求解柔性车间调度问题

Enhanced Harris Hawk optimization algorithm for solving flexible job shop scheduling problems

针对以最小化最大完工时间为优化目标的单目标柔性作业车间调度问题,本文提出了强化哈里斯鹰优化算法。通过Circle混沌映射改进算法初始种群的质量,提高算法的收敛速度;采用正余弦策略改进逃逸能量的变化方式,并将逃逸能量与跳跃强度相结合,以此提升算法的全局探索能力,预防算法陷入局部最优;使用柯西扰动的差分进化策略提高算法的局部搜索能力以及寻优性能。通过柔性作业车间调度问题典型算例的对比试验,验证了强化哈里斯鹰算法能够有效求解柔性作业车间调度问题。

For the single-objective flexible job shop scheduling problem with the optimization objective of minimizing the maximum completion time,this paper proposes the enhanced Harris Hawk optimization algorithm.The quality of the initial population of the algorithm is improved by Circle chaotic mapping to improve the convergence speed of the algorithm.A sine cosine strategy is used to improve the variation of escape energy,and the escape energy is combined with the jump strength to improve the global exploration ability of the algorithm and prevent the algorithm from falling into local optimum.The differential evolution strategy with Cauchy perturbation is used to improve the local search ability of the algorithm and the performance of the optimization search.Through comparative experiments with typical examples of flexible job shop scheduling problems,it has been verified that the enhanced Harris Hawk algorithm can effectively solve flexible job shop scheduling problems.