改进的人工蜂群算法在作业调度中的应用

MODIFIED ARTIFICIAL BEE COLONY ALGORITHM FOR JOB SCHEDULING PROBLEM

人工蜂群算法是一种模拟蜜蜂觅食行为的人工智能优化算法。作业调度问题是指在一个系统内通过某种方式分配工作以达到工作效率或资源分配最优。在本文中,将遗传算法的变异和杂交操作插到传统的人工蜂群算法中,从而提出一种改进的人工蜂群算法。变异操作在雇用蜂阶段后插入,杂交操作在跟随蜂阶段之后插入。实验表明,本文的改进人工蜂群算法在作业调度中的作用是有效的、显著的。

Artificial Bee Colony Algorithm （ABC） is an optimization algorithm based on the ntelligent foraging be- havior of honey bee swarm. The job scheduling wovk is the problem of assigning the jobs in the system in a man- ner that will optimize the overall performance of the application. In this paper, An Efficient artificial bee colony （ABC） algorithm, where the additional mutation and crossover operator of Genetic algorithm （GA） weve used in the classical ABC algorithm. The crossover operator after the employed bee phase and mutation operator after on- looker bee phase of ABC algorithm hawe been used. The simulated results show that ABC proves to be a better algorithm when applied to job scheduling problem.