Comparative Analysis of Genetic Algorithm and Ant Colony Algorithm on Solving Traveling Salesman Problem
- 1 July 2008
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE International Workshop on Semantic Computing and Systems
Abstract
Ant Colony Algorithm and Genetic Algorithm (GA), two bionic-inspired optimization algorithms, have great potentials to solve the combination optimization problems, respectively used in solving traveling salesman problem, but there are some shortcomings if only one of them is used to solve TSP. Performance comparative analysis have been done by using ACA and GA respectively in solving TSP in this paper. The experiments show the advantages and disadvantages used only ACA or GA, we can overcome the shortcomings if GA and ACA are combined to solve TSP and get faster convergent speed and more accurate results compared with only using ACA or GA.Keywords
This publication has 1 reference indexed in Scilit:
- Ant system: optimization by a colony of cooperating agentsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1996