International Journal of Computational Intelligence Systems

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Volume 9, Issue 6, December 2016, Pages 1174 - 1190

A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0–1 Knapsack Problems

Authors
Yanhong Feng1, qinfyh@163.com, Gai-Ge Wang2, 3, 4, 5, *, gaigewang@gmail.com gaigewang@163.com, Xiao-Zhi Gao6, xiao.z.gao@gmail.com
1School of Information Engineering, Hebei GEO University, Shijiazhuang, 050031, China
2School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China
3Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6R 2V4, Canada
4Institute of Algorithm and Big Data Analysis, Northeast Normal University, Changchun, 130117, China
5School of Computer Science and Information Technology, Northeast Normal University, Changchun, 130117, China
6Machine Vision and Pattern Recognition Laboratory, School of Engineering Science, Lappeenranta University of Technology, 53851 Lappeenranta, Finland
* Correspondence should be addressed to gaigewang@163.com
Corresponding Author
Received 2 February 2016, Accepted 1 July 2016, Available Online 1 December 2016.
DOI
10.1080/18756891.2016.1256577How to use a DOI?
Keywords
Cuckoo search; Global Harmony Search; 0–1 knapsack problems; Hybrid Encoding
Abstract

Cuckoo search (CS) is a novel biologically inspired algorithm and has been widely applied to many fields. Although some binary-coded CS variants are developed to solve 0–1 knapsack problems, the search accuracy and the convergence speed are still needed to further improve. According to the analysis of the shortcomings of the standard CS and the advantage of the global harmony search (GHS), a novel hybrid meta-heuristic optimization approach, called cuckoo search Algorithm with global harmony search (CSGHS), is proposed in this paper to solve 0–1 knapsack problems (KP) more effectively. In CSGHS, it is the combination of the exploration of GHS and the exploitation of CS that makes the CSGHS efficient and effective. The experiments conducted demonstrate that the CSGHS generally outperformed the binary cuckoo search, the binary shuffled frog-leaping algorithm and the binary differential evolution in accordance with the search accuracy and convergence speed. Therefore, the proposed hybrid algorithm is effective to solve 0–1 knapsack problems.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 6
Pages
1174 - 1190
Publication Date
2016/12/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1256577How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Yanhong Feng
AU  - Gai-Ge Wang
AU  - Xiao-Zhi Gao
PY  - 2016
DA  - 2016/12/01
TI  - A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0–1 Knapsack Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 1174
EP  - 1190
VL  - 9
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1256577
DO  - 10.1080/18756891.2016.1256577
ID  - Feng2016
ER  -