The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms
Many global optimization problems are presented as a black-box model, in which there is no information on the objective function properties. Traditional optimization algorithms usually can't effectively solve that kind of problems. Different heuristics and metaheuristics are usually applied in...
| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | English |
| Publicado em: |
EDP Sciences
2024-01-01
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| Colecção: | ITM Web of Conferences |
| Acesso em linha: | https://www.itm-conferences.org/articles/itmconf/pdf/2024/02/itmconf_hmmocs2023_04013.pdf |
| _version_ | 1827364598619045888 |
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| author | Sopov Anton Karaseva Tatiana |
| author_facet | Sopov Anton Karaseva Tatiana |
| author_sort | Sopov Anton |
| collection | DOAJ |
| description | Many global optimization problems are presented as a black-box model, in which there is no information on the objective function properties. Traditional optimization algorithms usually can't effectively solve that kind of problems. Different heuristics and metaheuristics are usually applied in that case. Evolutionary algorithms are one of the most popular and effective approaches to black-box optimization problems. However, it's hard to choose one specific method that will solve the given problem better than other algorithms. For dealing with this issue, self-adaptive schemes are usually implemented. In this paper we have investigated the performance of different PDP-type adaptive schemes using such popular evolutionary-based algorithms as Genetic Algorithm, Differential Evolution, and Particle Swarm Optimization. The experimental results on a set of benchmark problems have shown that investigated schemes can improve the performance compared with the performance of a stand-alone evolutionary algorithm. At the same time the choice of a scheme and its parameters affect the results. |
| first_indexed | 2024-03-08T08:13:33Z |
| format | Article |
| id | doaj.art-7f1f8f96069144bf84bbcff0dc5b80c7 |
| institution | Directory Open Access Journal |
| issn | 2271-2097 |
| language | English |
| last_indexed | 2024-03-08T08:13:33Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj.art-7f1f8f96069144bf84bbcff0dc5b80c72024-02-02T08:04:06ZengEDP SciencesITM Web of Conferences2271-20972024-01-01590401310.1051/itmconf/20245904013itmconf_hmmocs2023_04013The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithmsSopov Anton0Karaseva Tatiana1Reshetnev Siberian State University of Science and Technology, Institute of Informatics and TelecommunicationsSiberian Federal University, Department of Business Informatics and Business Process ModelingMany global optimization problems are presented as a black-box model, in which there is no information on the objective function properties. Traditional optimization algorithms usually can't effectively solve that kind of problems. Different heuristics and metaheuristics are usually applied in that case. Evolutionary algorithms are one of the most popular and effective approaches to black-box optimization problems. However, it's hard to choose one specific method that will solve the given problem better than other algorithms. For dealing with this issue, self-adaptive schemes are usually implemented. In this paper we have investigated the performance of different PDP-type adaptive schemes using such popular evolutionary-based algorithms as Genetic Algorithm, Differential Evolution, and Particle Swarm Optimization. The experimental results on a set of benchmark problems have shown that investigated schemes can improve the performance compared with the performance of a stand-alone evolutionary algorithm. At the same time the choice of a scheme and its parameters affect the results.https://www.itm-conferences.org/articles/itmconf/pdf/2024/02/itmconf_hmmocs2023_04013.pdf |
| spellingShingle | Sopov Anton Karaseva Tatiana The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms ITM Web of Conferences |
| title | The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms |
| title_full | The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms |
| title_fullStr | The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms |
| title_full_unstemmed | The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms |
| title_short | The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms |
| title_sort | comparison of different pdp type self adaptive schemes for the cooperation of ga de and pso algorithms |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2024/02/itmconf_hmmocs2023_04013.pdf |
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