¡¡Chinese Journal of Computers   Full Text
  TitleGood Point Set Based Genetic Algorithm
  AuthorsZHANG Ling£±£©£¬£²£© ZHANG Bo£²£©£¬£³£©
  Address£±£©(Key Laboratory of Intelligent Computing & Signal Processing, Institute of Artificial Intelligence, Anhui University, Hefei 230039) £²£©(Department of Computer Science and Technology, Tsinghua University, Beijing 100084) £³£©(State
  Year2001
  IssueNo.9(917-922)
  Abstract &
  Background
By analyzing the genetic algorithm(GA) based on its idea density model, the essence and characteristics of GA are given. It is shown that the GA is a guided random search and the guiding direction always aims at the family whose ancestors have schemata with high fitness. Based on the results, the crossover operation in GA is redesigned by using the principle of good point set in number theory. Then a new GA called good point set based GA is presented. The new GA is applied to optimization problems such as SAT,TSP, etc. Compared to other approaches for solving SAT, the simulation results show that the new GA has superiority in speed, accuracy and overcoming premature. The new interpretation of GA and the proposed good point set based GA provide a new way for investigating GA.
keywords Genetic Algorithm(GA), theory of good point set, Good point set based GA(GGA)