提出遗传算法和蚂蚁算法动态融合解决资源约束调度问题的方法.讨论资源约束调度过程中遗传算法的编码规则,蚂蚁算法中蚂蚁的概率选择方法和信息素更新规则,给出两种算法的动态切换条件及如何由遗传算法的调度结果产生蚂蚁算法的初始信息素分布等.实验数据表明本文方法的稳定性、平均运行时间和平均调度结果均优于单独的遗传算法和蚂蚁算法.
A resource constrained scheduling (RCS) method based on dynamic combination of genetic algorithm (GA) ana ant algorithm (AA) is proposed in this paper. The encoding method of GA and the probability selection and pheromone update rules of ants in AA are discussed for RCS. The dynamic switching condition of the two algorithms and how to generate the initial pheromone distribution of ant system (AS) from the scheduling results of AA for RCS is given. Experimental data for RCS indicate that the stability, the average execution time and the average scheduling results of our method are better than GA and AA respectively.