网格任务调度为多项式复杂程度的非确定性问题，其中所有非确定性多项式时间可解的判定问题，共同构成了NP类问题。如何快速地找到全局最优解是网格任务调度的难点所在。而遗传算法在验证猜测的正确性方面，具有自动获取和快速搜索的特性，是解决非线性问题的最优方案。本文主要对基于遗传算法的网格任务调度方法进行分析，通过网格任务调度模型构建、资源分配等操作，来完成遗传算法的仿真实验研究。

Grid task scheduling is a non-deterministic problem with polynomial complexity. All uncertain decision problems of polynomial time can constitute NP class problem. So how to quickly find the global optimal solution is the difficult point of grid task scheduling. The genetic algorithm, which has the characteristics of automatic acquisition and fast search, is the best solution to solve the nonlinear problem. This paper mainly analyzes the grid task scheduling method based on genetic algorithm, and completes the simulation experiment research of genetic algorithm through the grid task scheduling model construction, resource allocation and other operations.