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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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 |
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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 |
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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 |
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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 |
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2008 |
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http://hdl.handle.net/10356/13118 |
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1772828016383098880 |