An Improved Evolutionary Algorithm with New Genetic Operation for Optimization Problem

Abstract

An improved evolutionary algorithm (SCAGA) is proposed in this paper for solving optimization problem. In order to control genetic operations in an effective range, the new algorithm regulate both of the crossover probability and mutation probability with the iteration process. In addition, SCAGA presents a new crossover strategy that restricts the cross of the chromosomes to some extent to protect good genes schema. We also perform the schema theorem on the algorithm process to analyze the working mechanism of SCAGA, and we conclude that the new algorithm is effective. According to experiment results for some test functions and TSP problems, SCAGA have a high performance in both constrained an unconstrained optimization problems. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4785