A Novel Evolutionary Algorithm with Improved Genetic Operator and Crossover Strategy

Abstract

An improved evolutionary algorithm (SCAGA) is proposed in this paper. The algorithm is based on new population initialization method and genetic operator. SCAGA adopts the crossover probability and mutation probability that vary with the increase of evolution generation in order to control genetic operations in an effective range. Meanwhile, SCAGA presents a new crossover strategy that restricts the cross of the chromosomes to some extent to protect good genes schema. The schema theorem is employed in the algorithm to analyze the working mechanism of SCAGA. According to experiment results for test functions and TSP problems, SCAGA is effective.