Time Planning And Evolution Of Computing The Number Of Applied Research

In this paper, We further discuss the application of Evolutionary Algorithm(EA) and Time Programming on the arrangement of sports items in track and field game. Here we focus on four topics: Standard Genetic Algorithm(GA),Good-point set Genetic Algorithm(GGA),Time Programming.(TP),Genetic Programming(GP),and we can learn and understand the principle and mechanism of EA and TP from them.Evolutionary Algorithm is an important subject in Artificial Intelligence research field. Many methods have been put forward by this time. All these methods are based on Biology Evolutionary theory of Darwen that the superior individual will be held and the inferior one will be eliminated. Genetic Algorithm is the most representative and preliminary method of them. We introduced the basic principles,operations,steps, common characteristics, develop history and application field of Genetic Algorithm in the paper.Good-point based Genetic Algorithm is a more efficient method based on Genetic Algorithm theory. This method adopts good-point set in Number-theoretic to construct new genetic operator and applies merits of good-point set to improve efficiency and convergence of algorithms. GGA has been applied successfully in some optimization applications,for example Knapsack Problem and Travelling Salesman Problem etc. In second chapter, we first introduce how to construct a goog-point set and the steps to solve problem.then give an example of how to arrange sports items in a track and field game to use GGA in the end.Genetic Programming is another method of Evolutionary Algorithm that use formula to represent actions of Artificial Intelligence. It overcomes the shortcoming that the structure of chromosome is too simple. It spreads the application field of Evolutionary Algorithm by improving genetic operations. In the last chapter,we describe the principles of Genetic Programming on the basis of tree shapechromosome and give an example of solving similar function problem.Time Programming is a special field of Artificial Intelligence. It uses time relation constraint for reasoning. We discuss the R_schedule algorithm at the base of single ingredient time relation,and put forward a new idea of attempting to using Genetic algorithm to solve R_schedule problem at multiple ingredient time relation. Then we give an algorithm of solving the optimize single ingredient decomposition of multiple ingredient time relation,and prove the algoritm's maturity in mathematics. At last we give an example of the arrangement of sports items in track and field game to demonstrate the feasibility of this new idea.