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Progress in Artificial Intelligence
Erschienen in: Progress in Artificial Intelligence 3/2016

01.08.2016 | Regular Paper

An improved structure of genetic algorithms for global optimisation

verfasst von: Son Duy Dao, Kazem Abhary, Romeo Marian

Erschienen in: Progress in Artificial Intelligence | Ausgabe 3/2016

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Abstract

Genetic Algorithm (GA) is one of the most general global optimisation solution methods used in countless number of works. However, like other search techniques, GA has weak theoretical guarantee of global optimal solution and can only offer a probabilistic guarantee. Having a GA capable of searching for the global optimal solution with very high success probability is always desirable. In this paper, an innovative structure of GA, in which adaptive restarting and chromosome elite transferring strategies are harmoniously integrated together, is proposed to improve the success rate of achieving global optimal solution of the algorithm. The robustness of the proposed GA structure is demonstrated through a number of case studies.
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Metadaten
Titel
An improved structure of genetic algorithms for global optimisation
verfasst von
Son Duy Dao
Kazem Abhary
Romeo Marian
Publikationsdatum
01.08.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Progress in Artificial Intelligence / Ausgabe 3/2016
Print ISSN: 2192-6352
Elektronische ISSN: 2192-6360
DOI
https://doi.org/10.1007/s13748-016-0091-3

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