# 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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