Niching mechanisms in evolutionary computations
Zdzisław Kowalczuk; Tomasz Białaszewski
International Journal of Applied Mathematics and Computer Science (2006)
- Volume: 16, Issue: 1, page 59-84
- ISSN: 1641-876X
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topKowalczuk, Zdzisław, and Białaszewski, Tomasz. "Niching mechanisms in evolutionary computations." International Journal of Applied Mathematics and Computer Science 16.1 (2006): 59-84. <http://eudml.org/doc/207778>.
@article{Kowalczuk2006,
abstract = {Different types of niching can be used in genetic algorithms (GAs) or evolutionary computations (ECs) to sustain the diversity of the sought optimal solutions and to increase the effectiveness of evolutionary multi-objective optimization solvers. In this paper four schemes of niching are proposed, which are also considered in two versions with respect to the method of invoking: a continuous realization and a periodic one. The characteristics of these mechanisms are discussed, while as their performance and effectiveness are analyzed by considering exemplary multi-objective optimization tasks both of a synthetic and an engineering (FDI) design nature.},
author = {Kowalczuk, Zdzisław, Białaszewski, Tomasz},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {ranking; solutions diversity; genetic algorithms; multi-objective optimization; engineering designs; evolutionary computations; detection observers; Pareto-optimality; niching},
language = {eng},
number = {1},
pages = {59-84},
title = {Niching mechanisms in evolutionary computations},
url = {http://eudml.org/doc/207778},
volume = {16},
year = {2006},
}
TY - JOUR
AU - Kowalczuk, Zdzisław
AU - Białaszewski, Tomasz
TI - Niching mechanisms in evolutionary computations
JO - International Journal of Applied Mathematics and Computer Science
PY - 2006
VL - 16
IS - 1
SP - 59
EP - 84
AB - Different types of niching can be used in genetic algorithms (GAs) or evolutionary computations (ECs) to sustain the diversity of the sought optimal solutions and to increase the effectiveness of evolutionary multi-objective optimization solvers. In this paper four schemes of niching are proposed, which are also considered in two versions with respect to the method of invoking: a continuous realization and a periodic one. The characteristics of these mechanisms are discussed, while as their performance and effectiveness are analyzed by considering exemplary multi-objective optimization tasks both of a synthetic and an engineering (FDI) design nature.
LA - eng
KW - ranking; solutions diversity; genetic algorithms; multi-objective optimization; engineering designs; evolutionary computations; detection observers; Pareto-optimality; niching
UR - http://eudml.org/doc/207778
ER -
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