Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2013, Special Issue (2013), Article ID 912056, 9 pages.

A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem

Hongqing Zheng and Yongquan Zhou

Full-text: Open access

Abstract

Taking inspiration from an organizational evolutionary algorithm for numerical optimization, this paper designs a kind of dynamic population and combining evolutionary operators to form a novel algorithm, a cooperative coevolutionary cuckoo search algorithm (CCCS), for solving both unconstrained, constrained optimization and engineering problems. A population of this algorithm consists of organizations, and an organization consists of dynamic individuals. In experiments, fifteen unconstrained functions, eleven constrained functions, and two engineering design problems are used to validate the performance of CCCS, and thorough comparisons are made between the CCCS and the existing approaches. The results show that the CCCS obtains good performance in the solution quality. Moreover, for the constrained problems, the good performance is obtained by only incorporating a simple constraint handling technique into the CCCS. The results show that the CCCS is quite robust and easy to use.

Article information

Source
J. Appl. Math., Volume 2013, Special Issue (2013), Article ID 912056, 9 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394807370

Digital Object Identifier
doi:10.1155/2013/912056

Mathematical Reviews number (MathSciNet)
MR3094904

Citation

Zheng, Hongqing; Zhou, Yongquan. A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem. J. Appl. Math. 2013, Special Issue (2013), Article ID 912056, 9 pages. doi:10.1155/2013/912056. https://projecteuclid.org/euclid.jam/1394807370


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