Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/25963
Autoria: | Öztürk, E. Rocha, P. Sousa, F. Lima, M. Rodrigues, A. M. Ferreira, J. S. Nunes, A. C. Lopes, C. Oliveira, C. |
Editor: | Machado, J., Soares, F., Trojanowska, J., Yildirim, S., Vojtěšek, J., Rea, P., Gramescu, B., and Hrybiuk, O. O. |
Data: | 2022 |
Título próprio: | An application of Preference-Inspired Co-Evolutionary Algorithm to sectorization |
Título e volume do livro: | Innovations in Mechatronics Engineering II. Lecture Notes in Mechanical Engineering |
Paginação: | 257 - 268 |
Título do evento: | 2nd International Scientific Conference on Innovation in Engineering, ICIE 2022 |
ISSN: | 2195-4356 |
ISBN: | 978-3-031-09385-2 |
DOI (Digital Object Identifier): | 10.1007/978-3-031-09385-2_23 |
Palavras-chave: | Sectorization problems Co-evolutionary algorithms Many-objective optimisation |
Resumo: | Sectorization problems have significant challenges arising from the many objectives that must be optimised simultaneously. Several methods exist to deal with these many-objective optimisation problems, but each has its limitations. This paper analyses an application of Preference Inspired Co-Evolutionary Algorithms, with goal vectors (PICEA-g) to sectorization problems. The method is tested on instances of different size difficulty levels and various configurations for mutation rate and population number. The main purpose is to find the best configuration for PICEA-g to solve sectorization problems. Performancemetrics are used to evaluate these configurations regarding the solutions’ spread, convergence, and diversity in the solution space. Several test trials showed that big and medium-sized instances perform better with low mutation rates and large population sizes. The opposite is valid for the small size instances. |
Arbitragem científica: | yes |
Acesso: | Acesso Aberto |
Aparece nas coleções: | DMQGE-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Tamanho | Formato | |
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conferenceobject_89719.pdf | 817,01 kB | Adobe PDF | Ver/Abrir |
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