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Differential evolution with an individual-dependent mechanism
Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference of positions between individuals to perturb base vectors and thus generate new mutant individuals. However, the difference between the fitness values of individuals, which may be helpful to improve the pe...
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| Main Authors: | , , |
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| Format: | Default Article |
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2014
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| Online Access: | https://hdl.handle.net/2134/20904 |
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| _version_ | 1823269654985965568 |
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| author | Lixin Tang Yun Dong Jiyin Liu |
| author_facet | Lixin Tang Yun Dong Jiyin Liu |
| author_sort | Lixin Tang (6313061) |
| collection | Figshare |
| description | Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference of positions between individuals to perturb base vectors and thus generate new mutant individuals. However, the difference between the fitness values of individuals, which may be helpful to improve the performance of the algorithm, has not been used to tune parameters and choose mutation strategies. In this paper, we propose a novel variant of DE with an individual-dependent mechanism that includes an individual-dependent parameter (IDP) setting and an individual-dependent mutation (IDM) strategy. In the IDP setting, control parameters are set for individuals according to the differences in their fitness values. In the IDM strategy, four mutation operators with different searching characteristics are assigned to the superior and inferior individuals, respectively, at different stages of the evolution process. The performance of the proposed algorithm is then extensively evaluated on a suite of the 28 latest benchmark functions developed for the 2013 Congress on Evolutionary Computation special session. Experimental results demonstrate the algorithm's outstanding performance. |
| format | Default Article |
| id | rr-article-9501725 |
| institution | Loughborough University |
| publishDate | 2014 |
| record_format | Figshare |
| spelling | rr-article-95017252014-09-30T00:00:00Z Differential evolution with an individual-dependent mechanism Lixin Tang (6313061) Yun Dong (291897) Jiyin Liu (1253823) Other commerce, management, tourism and services not elsewhere classified Artificial intelligence not elsewhere classified Information systems not elsewhere classified Differential evolution (DE) Global numerical optimization Individual dependent Mutation strategy Parameter setting Information Systems Artificial Intelligence and Image Processing Business and Management not elsewhere classified Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference of positions between individuals to perturb base vectors and thus generate new mutant individuals. However, the difference between the fitness values of individuals, which may be helpful to improve the performance of the algorithm, has not been used to tune parameters and choose mutation strategies. In this paper, we propose a novel variant of DE with an individual-dependent mechanism that includes an individual-dependent parameter (IDP) setting and an individual-dependent mutation (IDM) strategy. In the IDP setting, control parameters are set for individuals according to the differences in their fitness values. In the IDM strategy, four mutation operators with different searching characteristics are assigned to the superior and inferior individuals, respectively, at different stages of the evolution process. The performance of the proposed algorithm is then extensively evaluated on a suite of the 28 latest benchmark functions developed for the 2013 Congress on Evolutionary Computation special session. Experimental results demonstrate the algorithm's outstanding performance. 2014-09-30T00:00:00Z Text Journal contribution 2134/20904 https://figshare.com/articles/journal_contribution/Differential_evolution_with_an_individual-dependent_mechanism/9501725 All Rights Reserved |
| spellingShingle | Other commerce, management, tourism and services not elsewhere classified Artificial intelligence not elsewhere classified Information systems not elsewhere classified Differential evolution (DE) Global numerical optimization Individual dependent Mutation strategy Parameter setting Information Systems Artificial Intelligence and Image Processing Business and Management not elsewhere classified Lixin Tang Yun Dong Jiyin Liu Differential evolution with an individual-dependent mechanism |
| title | Differential evolution with an individual-dependent mechanism |
| title_full | Differential evolution with an individual-dependent mechanism |
| title_fullStr | Differential evolution with an individual-dependent mechanism |
| title_full_unstemmed | Differential evolution with an individual-dependent mechanism |
| title_short | Differential evolution with an individual-dependent mechanism |
| title_sort | differential evolution with an individual-dependent mechanism |
| topic | Other commerce, management, tourism and services not elsewhere classified Artificial intelligence not elsewhere classified Information systems not elsewhere classified Differential evolution (DE) Global numerical optimization Individual dependent Mutation strategy Parameter setting Information Systems Artificial Intelligence and Image Processing Business and Management not elsewhere classified |
| url | https://hdl.handle.net/2134/20904 |