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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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2008
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| Online Access: | http://hdl.handle.net/10356/13118 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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