Grid Task Scheduling Based on Improved Genetic Algorithm
基于改进遗传算法的网格任务调度研究

Grid task scheduling is a NP-complete problem which concerns the scheduling of tasks and resources in a large scale, and thus a scheduling algorithm of high efficiency is rectuired. A grid task scheduling algorithm based on GA was proposed. In the process of population initialization, a new method which combines the min-min algorithm and the max-min algorithm was addressed, and in the evolution of the population a new criterion predicting the premature convergence was presented and the corresponding improved mutation was designed to avoid premature convergence. The simulation results show that this improved algorithm can solve the problem of grid task scheduling more effectively.