Academic Journal
Biased random-key genetic algorithm with local search applied to the maximum diversity problem
| العنوان: | Biased random-key genetic algorithm with local search applied to the maximum diversity problem |
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| المؤلفون: | Silva, Geiza, Leite, André, Ospina, Raydonal, Leiva, Víctor, Figueroa-Zúñiga, Jorge, Castro, Cecília |
| بيانات النشر: | Multidisciplinary Digital Publishing Institute (MDPI) |
| سنة النشر: | 2023 |
| المجموعة: | Universidade of Minho: RepositóriUM |
| مصطلحات موضوعية: | Biological diversity conservation, Random-key genetic algorithm, Evolutionary algorithms, Computational simulations, Ciências Naturais::Matemáticas, Educação de qualidade |
| الوصف: | The maximum diversity problem (MDP) aims to select a subset with a predetermined number of elements from a given set, maximizing the diversity among them. This NP-hard problem requires efficient algorithms that can generate high-quality solutions within reasonable computa tional time. In this study, we propose a novel approach that combines the biased random-key genetic algorithm (BRKGA) with local search to tackle the MDP. Our computational study utilizes a com prehensive set of MDPLib instances, and demonstrates the superior average performance of our proposed algorithm compared to existing literature results. The MDP has a wide range of practical applications, including biology, ecology, and management. We provide future research directions for improving the algorithm’s performance and exploring its applicability in real-world scenarios. ; This research was partially supported by the National Council for Scientific and Technological Development (CNPq) through grant 303192/2022-4 (R.O.), and Comissão de Aperfeiçoamento de Pessoal do Nível Superior (CAPES), from the Brazilian government; by FONDECYT, grant number 1200525 (V.L.), from the National Agency for Research and Development (ANID) of the Chilean government under the Ministry of Science and Technology, Knowledge, and Innovation; and by Portuguese funds through the CMAT - Research Centre of Mathematics of University of Minho, references UIDB/00013/2020, UIDP/00013/2020 (C.C.). |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2227-7390 |
| Relation: | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00013%2F2020/PT; info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00013%2F2020/PT; https://www.mdpi.com/2227-7390/11/14/3072; Silva, G.; Leite, A.; Ospina, R.; Leiva, V.; Figueroa-Zúñiga, J.; Castro, C. Biased Random-Key Genetic Algorithm with Local Search Applied to the Maximum Diversity Problem. Mathematics 2023, 11, 3072. https://doi.org/10.3390/math11143072; https://hdl.handle.net/1822/86364; 3072 |
| DOI: | 10.3390/math11143072 |
| الاتاحة: | https://hdl.handle.net/1822/86364 https://doi.org/10.3390/math11143072 |
| Rights: | info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.53F4CE56 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 22277390 |
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| DOI: | 10.3390/math11143072 |