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Biased random-key genetic algorithm with local search applied to the maximum diversity problem

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العنوان: Biased random-key genetic algorithm with local search applied to the maximum diversity problem
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
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