蚁群-鱼群混合算法在差异工件批调度中的应用  

Application of Ant Colony Hybrid Algorithm in Batch Scheduling of Differentiated Jobs

作　　者：吕顺风 马科 

机构地区：[1]中国科学技术大学管理学院,合肥230026

出　　处：《计算机系统应用》2018年第1期162-167,共6页Computer Systems & Applications

基　　金：国家自然科学基金(71671168)

摘　　要：调度问题是组合优化领域中一类重要的问题,批调度问题更是考虑了工件的尺寸和机器的容量,增加了调度的难度.本文针对差异工件批调度问题,把蚁群算法和鱼群算法相结合,提出了一种混合算法:引入鱼群算法中拥挤度的概念,并且与蚁群算法相结合,这不仅能避免算法早熟现象的发生,也加快了算法后期的收敛速度.通过负载率与利用率的比较,混合算法相对于单一的算法,有着更高的效率和更好的效果,能够使寻优个体更快的寻找到满意解.Scheduling is an important issue in the field complicated since it takes into consideration of workpieces scheduling problems with non-identical sizes, we propose of portfolio optimization, and batch scheduling is more sizes and machine capacity. In this study, to solve the batch a hybrid algorithm based on ant colony algorithm and fish swarm algorithm. By introducing the fish algorithm＇s swarm degree into the ant colony algorithm, the hybrid algorithm does not only avoid the premature, but also accelerates the convergence speed of the algorithm. In respect of load rate and utilization, the optimization algorithm has higher efficiency and achieves better results, because it can reduce searching time in finding optimal solution.

关 键 词：蚁群算法 拥挤度 批调度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]