title:
 
A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0-1 Knapsack Problems
publication:
 
IJCIS
volume-issue:   9 - 6
pages:   1174 - 1190
ISSN:
  1875-6883
DOI:
  doi:10.2991/10.1080/18756891.2016.1256577 (how to use a DOI)
author(s):
 
Yanhong Feng, Gai-Ge Wang, Xiao-Zhi Gao
publication date:
 
December 2016
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:
 
© The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
full text: