Krill herd algorithm based on cuckoo search for solving engineering optimization problems

Mohamed Abdel-Basset, Gai Ge Wang, Arun Kumar Sangaiah, Ehab Rushdy

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

This paper presents a hybrid krill herd (CSKH) approach to solve structural optimization problems. CSKH improved the Krill herd algorithm (KH) by combining KU/KA operator originated from cuckoo search algorithm (CS) with KH. In CSKH, a greedy selection scheme is used and often overtakes the original KH and CS. In addition, in order to further enhance the assessment of CSKH, a fraction of the worst krill is thrown away and substituted with newly randomly generated ones by KA operator at the end of each generation. The CSKH is applied to five real engineering problems to verify its performance. The experimental results have proven that CSKH algorithm is well capable of solving constrained engineering design problems more efficiently and effectively than the basic CS and KH algorithm.

Original languageEnglish
Pages (from-to)3861-3884
Number of pages24
JournalMultimedia Tools and Applications
Volume78
Issue number4
DOIs
Publication statusPublished - 1 Feb 2019
Externally publishedYes

Fingerprint

Dive into the research topics of 'Krill herd algorithm based on cuckoo search for solving engineering optimization problems'. Together they form a unique fingerprint.

Cite this