模糊人工蜂群算法的置换流水车间调度问题求解

Fuzzy Artificial Bees Colony Algorithm for Solving Permutation Flow Shop Scheduling Problem

针对传统人工蜂群算法早熟收敛问题,基于模糊化处理和蜂群寻优的特点,提出一种模糊人工蜂群算法。将模糊输入输出机制引入到算法中来保持蜜源访问概率的动态更新。根据算法计算过程中的不同阶段对蜜源访问概率有效调整,避免算法陷入局部极值。通过对置换流水车间调度问题的仿真实验和与其他算法的比较,表明本算法可行有效,有良好的鲁棒性。

Aiming at the premature convergence problem in traditional artificial bees colony algorithm, fuzzy artificial bees colony algorithm is proposed, which is based on the principles of fuzzy processing and bees colony behavior. Fuzzy inputs and fuzzy outputs are introduced into the algorithm to maintain dynamic updates of the nectar access probability. According to effective adjustment on nectar access probability during the different stages of algorithm calculation, the algorithm avoids local optima. Simulated tests of permutation flow shop scheduling problem and comparisons with other algorithms show the algorithm is feasible and effective and the algorithm has strong global optimization ability.