For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Improved Wolf Pack Algorithm Based on Differential Evolution Elite Set
Xiayang CHEN Chaojing TANG Jian WANG Lei ZHANG Qingkun MENG
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2018/07/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Fundamentals of Information Systems
Wolf Pack Algorithm (WPA), Differential Evolution (DE), swarm intelligence, evolutionary computation,
Full Text: PDF(507.5KB)
>>Buy this Article
Although Wolf Pack Algorithm (WPA) is a novel optimal algorithm with good performance, there is still room for improvement with respect to its convergence. In order to speed up its convergence and strengthen the search ability, we improve WPA with the Differential Evolution (DE) elite set strategy. The new proposed algorithm is called the WPADEES for short. WPADEES is faster than WPA in convergence, and it has a more feasible adaptability for various optimizations. Six standard benchmark functions are applied to verify the effects of these improvements. Our experiments show that the performance of WPADEES is superior to the standard WPA and other intelligence optimal algorithms, such as GA, DE, PSO, and ABC, in several situations.