改进的人工鱼群算法在置换Flow Shop调度中的应用

Application of Improved Artificial Fish Swarm Algorithm to Permutation Flow Shop Scheduling Problem

分析了人工鱼算法(AFSA)存在的不足,在保持AFSA算法基本行为的基础上,提出了在觅食行为过程中采用基于交换列表的排序法,在随机移动行为中采用自适应的小范围移动行为的改进人工鱼群算法。根据置换Flow Shop调度问题的数学模型,给出了基于改进的人工鱼群算法的置换Flow Shop调度问题的求解策略,并详细讨论了求解步骤。仿真实验结果表明:该算法具有较强的全局搜索能力、更高的搜索效率,同时验证了该算法的可行性和有效性。

Artificial fish swarm algorithm （AFSA） is a novel swarm intelligent optimization algorithm. A new intelligent optimization was involved for scheduling problems. By analyzing the disadvantages of AFSA, this paper presents an improved artificial fish swarm algorithm（IAFSA）. IAFSA adopts the order method based on exchanging list during the action of preying, and adopts an adaptive moving of small scale during the action of random move. According to the mathematic model of permutation flow shop scheduling, this paper provides the IAFSA-based solving strategy for the scheduling problem and discusses in detail the solving steps. The experiment results show that IAFSA has a stronger ability of global search and a better search efficiency, and it is feasible and valid.