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   Vol.E101-D   No.7   pp.1946-1949
Publication Date: 2018/07/01
Publicized: 2018/03/30
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDL8201
Type of Manuscript: LETTER
Category: Fundamentals of Information Systems
Wolf Pack Algorithm (WPA),  Differential Evolution (DE),  swarm intelligence,  evolutionary computation,  

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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.