人工鱼群算法与差分进化变异蟑螂算法动态融合及其在网格任务调度中的应用

摘要

In this paper, according to the analysis of characteristics of artificial fish swarm algorithm (AFSA) and cockroach swarm optimisation, an improved cockroach swarm optimisation is presented. Because of the introduction of differential evolution mutation and taboo table, the algorithm' s searching speed and global search ability are all improved. The dynamic fusion of the AFSA and the improved cockroach swarm optimisation is realised in the way of measuring the difference between the optimal individual and the elite individual in the population. Simulative experiment shows that such algorithm after the dynamic fusion can achieve better scheduling effect when applying it in grid task scheduling.%深入分析人工鱼群算法和蟑螂算法的特点基础,提出一种改进式蟑螂算法.将差分进化变异因子、禁忌表分别引入到蟑螂算法,加快了算法的搜索速度和获得全局最优解的能力.采用权衡种群中最优个体和精英个体之间的差异度的方式将改进后的蟑螂算法和人工鱼群算法动态融合.仿真实验表明将这种动态融合后的算法解决网格任务调度问题可以获得较好的调度效果.