An enhanced adaptive global‐best harmony search algorithm for continuous optimization problems

Engineering Reports

Amir H. Alavi¹  Hasan Yarmohamadi¹  Qianyun Zhang¹  Pengcheng Jiao² 

[1] Department of Civil and Environmental Engineering University of Pittsburgh PittsburghPA USA;Institute of Port, Coastal and Offshore Engineering, Ocean College Zhejiang University Zhoushan China;

关键词: continuous optimization;    global‐best harmony search;    global optimization;    harmony search algorithm;    metaheuristics;   

DOI  :  10.1002/eng2.12264

来源: DOAJ

【 摘 要 】

Abstract This paper presents an enhanced adaptive global‐best harmony search (EAGHS) to solve global continuous optimization problems. The global‐best HS (GHS) is one of the strongest versions of the classical HS algorithm that hybridizes the concepts of swarm intelligence and conventional HS. However, randomized selection of harmony in the permissible interval diverts the GHS algorithm from the global optimum. To address this issue, the proposed EAGHS method introduces a dynamic coefficient into the GHS algorithm to increase the search power in early iterations. Various complex and extensively‐applied benchmark functions are used to validate the developed EAGHS algorithm. The results indicate that the EAGHS algorithm offers faster convergence and better accuracy than the standard HS, GHS and other similar algorithms. Further analysis is performed to evaluate the sensitivity of the proposed method to the changes of parameters such as harmony memory consideration rate, harmony search memory, and larger dimensions.

【 授权许可】

Unknown