Convergence properties of non-crossover genetic algorithm

Dai Xiaoming Dai Xiaoming,Zou Runmin Zou Runmin,Huihe Shao Huihe Shao,Sun Rong Sun Rong,Feng Rui Feng Rui

doi:10.1109/wcica.2002.1021397

Convergence properties of non-crossover genetic algorithm

Dai Xiaoming Dai Xiaoming, Zou Runmin Zou Runmin + Show 3 more

https://doi.org/10.1109/wcica.2002.1021397

Copy DOI

Publication Date: Nov 7, 2002

Citations: 7

Affiliation: Shanghai Jiao Tong University, Central South University

#Canonical Genetic Algorithm #Selection Operators + Show 8 more

Abstract
Full-Text PDF
Similar Papers

Abstract

The canonical genetic algorithm (CGA) applies selection, crossover and mutation operators to solve difficult optimization problems. This paper introduces a new approach to CGA. It applies only mutation and selection operators. It is a non-crossover genetic algorithm (NCGA). The proof of global convergence of NCGA is presented in this paper. The simulation on the NP-complete traveling salesman problem (TSP) shows that NCGA is much faster than the CGA. In terms of computation efficiency, NCGA is a very promising approach. This paper casts doubt on the need of the crossover operator in GAs.

Full Text