Effective and Efficient ways of Hybridizing GA with various methods while reviewing a wide variety of Hybrid Genetic Approaches.

DOI

10.2991/icaise.2013.29How to use a DOI?

Keywords

Local search, genetic algorithm, hybrid, population, fitness, algorithms, Lamarckian

Abstract

Hybrid genetic algorithms significant interest over the decade are increasingly used to resolve real-world problems. Genetic algorithm’s ability to incorporate various techniques within its framework to produce a hybrid that secures the best from the blend. In this paper, different forms of integrations between genetic algorithms and various search and optimization techniques/methods will be focused on. This dissertation also aims to observe issues that acquire our consideration when designing a hybrid genetic algorithm that uses another search method as searching tools. Different approaches for employing these searching tool information and various mechanisms that acquire attaining a balance between global genetic algorithm and search tools.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nafisa Maqbool
AU  - Chaoyong Zhang
AU  - Mudabbir Baddir
PY  - 2013/08
DA  - 2013/08
TI  - Effective and Efficient ways of Hybridizing GA with various methods while reviewing a wide variety of Hybrid Genetic Approaches.
BT  - Proceedings of the 2013 The International Conference on Artificial Intelligence and Software Engineering (ICAISE 2013)
PB  - Atlantis Press
SP  - 137
EP  - 142
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaise.2013.29
DO  - 10.2991/icaise.2013.29
ID  - Maqbool2013/08
ER  -