An improved genetic algorithm based on gene pool for TSP

2Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Traveling salesman problem is a typical representative of combinatorial optimization problems. An improved Genetic algorithm is proposed for solving Traveling Salesman Problem (TSP). This Partheno-genetic algorithm employs only mutation and selection operators to produce the offspring, A new combinatory operator is designed combining the gene pool operator with inversion operator which ensures its strong searching capability. The gene pool directs the single-parent evolution and enhances the evolutionary speed. This algorithm simulates the recurrence of nature evolution process. Experiments based on 4 instances selected from TSPLIB are used to test the performance of this algorithm. They prove that it can reach the satisfying optimization at a faster speed. Especially, for the KroA100, the best path it finds is better than any other available one. © 2014 Springer International Publishing.

Cite

CITATION STYLE

APA

Zhang, J., & Liu, X. (2014). An improved genetic algorithm based on gene pool for TSP. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8351 LNCS, pp. 766–773). Springer Verlag. https://doi.org/10.1007/978-3-319-09265-2_78

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free