Global optimization of continuous problems using stochastic genetic algorithm

Z G Tu, Y Lu

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

Abstract / Description of output

In this paper, a stochastic genetic algorithm (StGA) technique is presented to deal with global optimization of continuous problems. In this algorithm, a novel coding scheme called "stochastic coding" is employed, so that the search space is explored in terms of stochastic regions towards the near-global solution. The effectiveness and efficiency of the algorithm are demonstrated through performing optimization on several test functions and the results are compared with the well established Fast Evolutionary Programming (FEP) technique in terms of the global optimization accuracy and the computational efficiency.

Original languageEnglish
Title of host publicationCEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1230-1236
Number of pages7
ISBN (Print)0-7803-7804-0
Publication statusPublished - 2003
EventCongress on Evolutionary Computation (CEC) - Canberra
Duration: 8 Dec 200312 Dec 2003

Conference

ConferenceCongress on Evolutionary Computation (CEC)
CityCanberra
Period8/12/0312/12/03

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