Domination landscape in evolutionary algorithms and its applications
Evolutionary algorithms (EAs) are usually required to solve problems based on domination relationship among solutions. Often, the domination relationship is almost the sole source of knowledge that EAs can utilize, especially when the problem solving engine concerned is taken as a black box. In this...
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sg-ntu-dr.10356-1512602021-06-14T06:56:04Z Domination landscape in evolutionary algorithms and its applications Hao, Guo-Sheng Lim, Meng-Hiot Ong, Yew-Soon Huang, Han Wang, Gai-Ge School of Electrical and Electronic Engineering School of Computer Science and Engineering Engineering::Computer science and engineering Domination Relationship Evolutionary algorithms (EAs) are usually required to solve problems based on domination relationship among solutions. Often, the domination relationship is almost the sole source of knowledge that EAs can utilize, especially when the problem solving engine concerned is taken as a black box. In this paper, the domination landscape (DL), onto which an optimization problem (OP) can be mapped, is introduced. A DL may correspond to a cluster of OPs, implying that a class of OPs may have the same DL. To illustrate DL, we consider its representation as a directed graph, with its corresponding matrix and function. Of the various properties of DL, the domination-preserving property is used for the analysis of DL-equivalent OPs, and for the basis for classification of OPs. Taking DL as a tool for theoretical analysis, parameters determination for fitness scaling, the convergence property of EAs and the analysis of robustness in light of fitness noise are presented. The study of DL in this paper establishes the necessary theoretical foundation for future applications of DL equality and similarity based optimization. 2021-06-14T06:56:04Z 2021-06-14T06:56:04Z 2019 Journal Article Hao, G., Lim, M., Ong, Y., Huang, H. & Wang, G. (2019). Domination landscape in evolutionary algorithms and its applications. Soft Computing, 23(11), 3563-3570. https://dx.doi.org/10.1007/s00500-018-3206-x 1432-7643 0000-0002-5962-0832 https://hdl.handle.net/10356/151260 10.1007/s00500-018-3206-x 2-s2.0-85045832738 11 23 3563 3570 en Soft Computing © 2018 Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved. |
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Engineering::Computer science and engineering Domination Relationship Hao, Guo-Sheng Lim, Meng-Hiot Ong, Yew-Soon Huang, Han Wang, Gai-Ge Domination landscape in evolutionary algorithms and its applications |
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Evolutionary algorithms (EAs) are usually required to solve problems based on domination relationship among solutions. Often, the domination relationship is almost the sole source of knowledge that EAs can utilize, especially when the problem solving engine concerned is taken as a black box. In this paper, the domination landscape (DL), onto which an optimization problem (OP) can be mapped, is introduced. A DL may correspond to a cluster of OPs, implying that a class of OPs may have the same DL. To illustrate DL, we consider its representation as a directed graph, with its corresponding matrix and function. Of the various properties of DL, the domination-preserving property is used for the analysis of DL-equivalent OPs, and for the basis for classification of OPs. Taking DL as a tool for theoretical analysis, parameters determination for fitness scaling, the convergence property of EAs and the analysis of robustness in light of fitness noise are presented. The study of DL in this paper establishes the necessary theoretical foundation for future applications of DL equality and similarity based optimization. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Hao, Guo-Sheng Lim, Meng-Hiot Ong, Yew-Soon Huang, Han Wang, Gai-Ge |
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Article |
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Hao, Guo-Sheng Lim, Meng-Hiot Ong, Yew-Soon Huang, Han Wang, Gai-Ge |
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Hao, Guo-Sheng |
title |
Domination landscape in evolutionary algorithms and its applications |
title_short |
Domination landscape in evolutionary algorithms and its applications |
title_full |
Domination landscape in evolutionary algorithms and its applications |
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Domination landscape in evolutionary algorithms and its applications |
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Domination landscape in evolutionary algorithms and its applications |
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domination landscape in evolutionary algorithms and its applications |
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2021 |
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https://hdl.handle.net/10356/151260 |
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