Unconventional initialization methods for differential evolution

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86092931" target="_blank" >RIV/61989100:27240/13:86092931 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.amc.2012.10.053" target="_blank" >http://dx.doi.org/10.1016/j.amc.2012.10.053</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.amc.2012.10.053" target="_blank" >10.1016/j.amc.2012.10.053</a>

Result language
angličtina
Original language name
Unconventional initialization methods for differential evolution
Original language description
The crucial role played by the initial population in a population-based heuristic optimization cannot be neglected. It not only affects the search for several iterations but often also has an influence on the final solution. If the initial population itself has some knowledge about the potential regions of the search domain then it is quite likely to accelerate the rate of convergence of the optimization algorithm. In the present study we propose two schemes for generating the initial population of differential evolution (DE) algorithm. These schemes are based on quadratic interpolation (QI) and nonlinear simplex method (NSM) in conjugation with computer generated random numbers. The idea is to construct a population that is biased towards the optimumsolution right from the very beginning of the algorithm. The corresponding algorithms named as QIDE (using quadratic interpolation) and NSDE (using non linear simplex method), are tested on a set of 20 traditional benchmark problems with
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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