An Improved ACS Algorithm for the Solutions of Larger TSP Problems
Artificial Intelligence
2013-04-16 v1 Data Structures and Algorithms
Neural and Evolutionary Computing
Abstract
Solving large traveling salesman problem (TSP) in an efficient way is a challenging area for the researchers of computer science. This paper presents a modified version of the ant colony system (ACS) algorithm called Red-Black Ant Colony System (RB-ACS) for the solutions of TSP which is the most prominent member of the combinatorial optimization problem. RB-ACS uses the concept of ant colony system together with the parallel search of genetic algorithm for obtaining the optimal solutions quickly. In this paper, it is shown that the proposed RB-ACS algorithm yields significantly better performance than the existing best-known algorithms.
Keywords
Cite
@article{arxiv.1304.3763,
title = {An Improved ACS Algorithm for the Solutions of Larger TSP Problems},
author = {Md. Rakib Hassan and Md. Kamrul Hasan and M. M. A. Hashem},
journal= {arXiv preprint arXiv:1304.3763},
year = {2013}
}