Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
386482 | Expert Systems with Applications | 2010 | 11 Pages |
Abstract
Ant Colony Optimization (ACO) is a bioinspired metaheuristic based on ants foraging used to solve different classes of problems. In this paper, we show how, using a Two-Stage approach the quality of the solutions of ACO is improved. The Two-Stage approach can be applied to different ACO. The performance of this new approach is studied in the Traveling Salesman Problem and Quadratic Assignment Problem. The experimental results show that the obtained solutions are improved both problems using the Two-Stage approach. Several statistical procedures are applied to show the effect of this new approach.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Amilkar Puris, Rafael Bello, Francisco Herrera,