摘要
经常用于各种最优化处理过程的蚁群算法具有无法解决数据分类、动态请求、在线事务处理等一系列问题,严重时还可能发生停滞状况.在分析蚁群参数、参数选择、最优调度等问题的基础上,提出一种遗传算子结合蚂蚁任务分配模型的混合蚁群算法.仿真实验表明,这种算法在求解多处理机问题时,能在较短的时间内得到较优的调度策略,且该算法具有良好的有效性和收敛性.
The ant colony algorithm commonly used [n the optimization process has a series of problems. It is unable to solve data classification, dynamic request and no-online transaction processing. Sometimes, it turns out to be stagnant. Based on the analysis of ant colony algorithm parameters, this paper parameter selection and optimal scheduling, presents an ant colony algorithm combining genetic operators with the ant task allocation model. The simulation experiment shows that this algorithm can get a better scheduling strategy in a relatively short period of time when solving multiproeessor problems, and it has good effectiveness and convergence.
出处
《湖南工程学院学报(自然科学版)》
2016年第2期37-40,共4页
Journal of Hunan Institute of Engineering(Natural Science Edition)
关键词
多处理机问题
蚁群算法
遗传算子
muhiprocessor problem
Hybrid ant colony algorithm
genetic operator