A novel hybrid algorithm based on particle swarm and ant colony optimization for finding the global minimum
Küçük Resim Yok
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCIENCE INC
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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. (C) 2012 Elsevier Inc. All rights reserved.
Açıklama
Anahtar Kelimeler
Particle swarm optimization, Ant colony optimization, Hybrid metaheuristic, Global minimum
Kaynak
APPLIED MATHEMATICS AND COMPUTATION
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
219
Sayı
4
