基于蚁群优化和遗传操作的混合方法

A Hybrid Approach Based on Ants Colony Optimization(ACO) and Genetic Operators

尽管蚁群优化算法(ACO)在优化计算中已得到了很多应用,但在进行大规模优化时,其收敛时间过长仍是应用该算法的一个瓶颈.为了确保资源利用完成时间最小化和完成用户指定的最终期限延迟最小化,找到一个优化的调度方法,在计算网格中针对资源分配和调度提出了基于蚁群优化和遗传操作的混合方法.

Despite the numerous applications of ACO（ant colony optimization）algorithm in optimization computation, it remains a computational bottleneck that the ACO algorithm costs too much time in order to find an optimal solution for large-scaled optimization problems. The objective is to find an optimal schedule which will minimize the makespan so as to ensure the proper utilization of the resources and minimize.the delay in achieving user specified deadlines. A hybrid approach based on ACO and Genetic operators is proposed for resource allocation and scheduling in computational grids.