Stochastic genetic strategy in multi-objectives optimization

The approaches to tackling optimization problems of multiple-objectives can be classified into 3 categories. In the first category, a problem of n number of objectives is formulated as an «-stage problem with each stage being a single objective problem. At each stage, the technique will concentrate...

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Main Author: Gwee, Bah Hwee.
Other Authors: Lim, Meng Hiot
Format: Theses and Dissertations
Language:English
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/13118
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-131182023-07-04T15:06:57Z Stochastic genetic strategy in multi-objectives optimization Gwee, Bah Hwee. Lim, Meng Hiot School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity The approaches to tackling optimization problems of multiple-objectives can be classified into 3 categories. In the first category, a problem of n number of objectives is formulated as an «-stage problem with each stage being a single objective problem. At each stage, the technique will concentrate on searching for the best point to achieve a particular objective. For the second category of techniques, all the objectives of a problem are considered together with the goal of finding a good solution which achieves all the objectives simultaneously. The third category of approaches involves finding all the efficient solutions or non-inferior solutions from which the solution is chosen. Doctor of Philosophy (EEE) 2008-10-20T07:14:33Z 2008-10-20T07:14:33Z 1998 1998 Thesis http://hdl.handle.net/10356/13118 en 124 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity
spellingShingle DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity
Gwee, Bah Hwee.
Stochastic genetic strategy in multi-objectives optimization
description The approaches to tackling optimization problems of multiple-objectives can be classified into 3 categories. In the first category, a problem of n number of objectives is formulated as an «-stage problem with each stage being a single objective problem. At each stage, the technique will concentrate on searching for the best point to achieve a particular objective. For the second category of techniques, all the objectives of a problem are considered together with the goal of finding a good solution which achieves all the objectives simultaneously. The third category of approaches involves finding all the efficient solutions or non-inferior solutions from which the solution is chosen.
author2 Lim, Meng Hiot
author_facet Lim, Meng Hiot
Gwee, Bah Hwee.
format Theses and Dissertations
author Gwee, Bah Hwee.
author_sort Gwee, Bah Hwee.
title Stochastic genetic strategy in multi-objectives optimization
title_short Stochastic genetic strategy in multi-objectives optimization
title_full Stochastic genetic strategy in multi-objectives optimization
title_fullStr Stochastic genetic strategy in multi-objectives optimization
title_full_unstemmed Stochastic genetic strategy in multi-objectives optimization
title_sort stochastic genetic strategy in multi-objectives optimization
publishDate 2008
url http://hdl.handle.net/10356/13118
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