Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
392741 | Information Sciences | 2014 | 18 Pages |
Abstract
Recently, Gandomi and Alavi proposed a meta-heuristic optimization algorithm, called Krill Herd (KH). This paper introduces the chaos theory into the KH optimization process with the aim of accelerating its global convergence speed. Various chaotic maps are considered in the proposed chaotic KH (CKH) method to adjust the three main movements of the krill in the optimization process. Several test problems are utilized to evaluate the performance of CKH. The results show that the performance of CKH, with an appropriate chaotic map, is better than or comparable with the KH and other robust optimization approaches.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Gai-Ge Wang, Lihong Guo, Amir H. Gandomi, Guo-Sheng Hao, Heqi Wang,