Researches On The Schema-Based Algorithm

Genetic algorithm (GA) is one of adaptive stochastic algorithms for global optimum based on evolutionary and mutation theories. Because of its capacity of global searching, it is applied more and more to many scientific fields, but it still suffers from theory and performance. So more studies and improvements should be carried out to improve its performance because of its large value in theory research and practical application. In this thesis, the author extends crossover operators and schema theorem and attempts to avail the coding of genetic algorithms and creates a new algorithm, that is, schema-based algorithm. The significative conclusions are deduced by numerical simulation examples.The main context of this paper consists of five parts. In chapter 1, we introduce the history and status of problems that this paper presents. In chapter 2, we discuss some necessary mathematical preliminaries, some basic concepts and theories of SGA, moreover, extended studies concerning crossover and schema theorem are introduced in the part. In chapter 3 present schema-based GA, and in chapter 4, we give a numerical example and the results of the numerical simulation examples. At last, in chapter 5,we summarize the whole paper and look into the future of schema-based algorithm.