TY - JOUR
T1 - Krill herd algorithm based on cuckoo search for solving engineering optimization problems
AU - Abdel-Basset, Mohamed
AU - Wang, Gai Ge
AU - Sangaiah, Arun Kumar
AU - Rushdy, Ehab
N1 - Funding Information:
Acknowledgements This work was supported by the Natural Science Foundation of Jiangsu Province (No. BK20150239), National Natural Science Foundation of China (No. 61503165, No. 61673196, and No. 61402207), and The Open Research Fund of Sichuan Key Laboratory for Nature Gas and Geology (No.2015trqdz04).
Publisher Copyright:
© 2017, Springer Science+Business Media New York.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - 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.
AB - 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.
KW - Elitism scheme
KW - Engineering design problems
KW - Krill herd
KW - Lévy flight distribution
UR - http://www.scopus.com/inward/record.url?scp=85019633677&partnerID=8YFLogxK
U2 - 10.1007/s11042-017-4803-x
DO - 10.1007/s11042-017-4803-x
M3 - Article
AN - SCOPUS:85019633677
SN - 1380-7501
VL - 78
SP - 3861
EP - 3884
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 4
ER -