Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4629498 | Applied Mathematics and Computation | 2012 | 7 Pages |
Abstract
This paper presents a novel hybrid algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) and called hybrid ant particle optimization algorithm (HAP) to find global minimum. In the proposed method, ACO and PSO work separately at each iteration and produce their solutions. The best solution is selected as the global best of the system and its parameters are used to select the new position of particles and ants at the next iteration. The performance of proposed method is compared with PSO and ACO on the benchmark problems and better quality results are obtained by HAP algorithm.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Mustafa Servet Kıran, Mesut Gündüz, Ãmer Kaan Baykan,