A modified cuckoo search algorithm for dynamic optimization problems

Yuta Umenai, Fumito Uwano, Yusuke Tajima, Masaya Nakata, Hiroyuki Sato, Keiki Takadama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

This paper proposes a simple modification of the Cuckoo Search called CS for a dynamic environment. In this paper, we consider a dynamic optimization problem where the global optimum can be cyclically changed depending on time. Our modified CS algorithm holds good candidates in order to effectively explore the search space near those candidates with an intensive local search. Our first experiment tests the prosed method on a set of static optimization problems, which aims at evaluating the potential performance of the proposed method. Then, we apply it to a dynamic optimization problem. Experimental results on the static problems show that the proposed method derives a better performance than the conventional method, which suggest the proposed method potentially has a good capability of finding a good solution. On the dynamic problem, the proposed method also performs well while the conventional method fails to find a better solution.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1757-1764
Number of pages8
ISBN (Electronic)9781509006229
DOIs
Publication statusPublished - Nov 14 2016
Externally publishedYes
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: Jul 24 2016Jul 29 2016

Publication series

Name2016 IEEE Congress on Evolutionary Computation, CEC 2016

Conference

Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016
CountryCanada
CityVancouver
Period7/24/167/29/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Modelling and Simulation
  • Computer Science Applications
  • Control and Optimization

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