Research On The Intelligent Optimization Method For Grid Rescource Scheduling Problem

Intelligent Optimization is a kind of new technology, which focuses on the research of what kind of solution is the best and how to find the best solution. With the development of science and technology, a growing number of scholars pay attend to this field, and specially in recent decades, the fast development of computer technology provides effective tools to the optimization and makes a rapidly improvement.This paper studies the principle of intelligent optimization algorithms and its application in the task scheduling problem on the grid applications. Of many Optimization algorithms the main study are genetic algorithms, simulated annealing algorithm, and predatory search algorithm. Different research methods are used based on the character of intelligent optimization algorithms in this paper. For example, the genetic algorithm focuses on the relationship between the optimization results and the parameters, such as mutation probability, group scale, etc. The simulated annealing algorithm studies the influence on the initial temperature. And the predatory search studies the difference between traditional predatory search algorithm and modified predatory search algorithm. Hence, the research on optimization algorithm is of both theoretic significance and practical value.This paper consists of three parts. Firstly, it gives a briefly introduction to the task scheduling problem of the grid applications. Secondly, this paper introduces some typical intelligent optimization algorithms theories, implements and application on the task scheduling problem of the grid application, and at the same time, gives some comments on these intelligent optimization algorithms and shows the way on how to improve them. At last, this paper gives a summarization and prospect on those intelligent optimization algorithms.