IVF/SPEA2: Estudo Preliminar de um Algoritmo Evolutivo Híbrido para Otimização Multiobjetivo
Resumo
Este artigo apresenta o IVF/SPEA2, um algoritmo evolutivo multiobjetivo híbrido que integra o procedimento de Fertilização in Vitro ao SPEA2, visando aprimorar a convergência e diversidade das soluções. Realiza-se uma avaliação controlada usando o SPEA2 canônico como linha de base nas suítes ZDT, DTLZ, WFG e MaF. Os resultados, validados pela métrica Inverted Generational Distance (IGD) e pelo teste de Wilcoxon, demonstram ganhos estatisticamente significativos. O estudo evidencia o potencial da hibridização proposta e corrobora a possibilidade de avanço da pesquisa por novas experimentações.
Palavras-chave:
IVF/SPEA2, Algoritmo Evolutivo Híbrido, Otimização Multiobjetivo, Convergência, Diversidade
Referências
Zitzler, E., Laumanns, M., & Thiele, L. (2001). SPEA2: Improving the Strength Pareto Evolutionary Algorithm. TIK-Report 103, ETH Zurich.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions.
Zhang, Q., & Li, H. (2007). MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Transactions on Evolutionary Computation.
Camilo-Junior, C. G., & Yamanaka, K. (2011). In Vitro Fertilization Genetic Algorithm. In Evolutionary Algorithms (Chapter 4, pp. 1–14). InTech.
Sampaio, S. M., & Camilo-Junior, C. G. (2017). IVF/NSGA-II: In Vitro Fertilization Method Coupled to NSGA-II. In 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1–6). IEEE.
Sampaio, S. M., & Camilo-Junior, C. G. (2019). IVF/GDE3: In Vitro Fertilization Method Coupled to GDE3. In 2019 IEEE Congress on Evolutionary Computation (CEC)
Huband, S., Hingston, P., Barone, L., & While, L. (2006). A Review of Multiobjective Test Problems and a Scalable Test Problem Toolkit. IEEE Transactions.
Tian, Y., Cheng, R., Zhang, X., Li, M., & Jin, Y. (2019). Diversity Assessment of Multi-Objective Evolutionary Algorithms: Performance Metric and Benchmark Problems. IEEE Computational Intelligence Magazine, 14(3), 61–74.
Tian, Y., Cheng, R., Zhang, X., & Jin, Y. (2017). PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization. IEEE Computational .
Li, M., Yang, S., & Liu, X. (2013). Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization. IEEE Transactions.
Jiao, R., Xue, B., & Zhang, M. (2022). A Multiform Optimization Framework for Constrained Multiobjective Optimization. IEEE Transactions on Cybernetics.
Hu, Y., He, X., Jiang, W., & Guo, X. (2024). Studying Power IoT Edge Computing Server Layout Methods Based on SPEA2. In 2024 International Conference on Language Technology and Digital Humanities (LTDH). Bhubaneswar, India: IEEE.
Sampaio, S. M., Dantas, A., & Camilo-Junior, C. G. (2023). IVF/NSGA-III – In Vitro Fertilization Method Coupled to NSGA-III. In Proceedings of the 2023 IEEE Congress on Evolutionary Computation (CEC) (pp. 1–8). Chicago, IL, USA: IEEE.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions.
Zhang, Q., & Li, H. (2007). MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Transactions on Evolutionary Computation.
Camilo-Junior, C. G., & Yamanaka, K. (2011). In Vitro Fertilization Genetic Algorithm. In Evolutionary Algorithms (Chapter 4, pp. 1–14). InTech.
Sampaio, S. M., & Camilo-Junior, C. G. (2017). IVF/NSGA-II: In Vitro Fertilization Method Coupled to NSGA-II. In 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1–6). IEEE.
Sampaio, S. M., & Camilo-Junior, C. G. (2019). IVF/GDE3: In Vitro Fertilization Method Coupled to GDE3. In 2019 IEEE Congress on Evolutionary Computation (CEC)
Huband, S., Hingston, P., Barone, L., & While, L. (2006). A Review of Multiobjective Test Problems and a Scalable Test Problem Toolkit. IEEE Transactions.
Tian, Y., Cheng, R., Zhang, X., Li, M., & Jin, Y. (2019). Diversity Assessment of Multi-Objective Evolutionary Algorithms: Performance Metric and Benchmark Problems. IEEE Computational Intelligence Magazine, 14(3), 61–74.
Tian, Y., Cheng, R., Zhang, X., & Jin, Y. (2017). PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization. IEEE Computational .
Li, M., Yang, S., & Liu, X. (2013). Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization. IEEE Transactions.
Jiao, R., Xue, B., & Zhang, M. (2022). A Multiform Optimization Framework for Constrained Multiobjective Optimization. IEEE Transactions on Cybernetics.
Hu, Y., He, X., Jiang, W., & Guo, X. (2024). Studying Power IoT Edge Computing Server Layout Methods Based on SPEA2. In 2024 International Conference on Language Technology and Digital Humanities (LTDH). Bhubaneswar, India: IEEE.
Sampaio, S. M., Dantas, A., & Camilo-Junior, C. G. (2023). IVF/NSGA-III – In Vitro Fertilization Method Coupled to NSGA-III. In Proceedings of the 2023 IEEE Congress on Evolutionary Computation (CEC) (pp. 1–8). Chicago, IL, USA: IEEE.
Publicado
04/12/2025
Como Citar
ZAMBRANO, Pedro Sanches; S., Eduardo F.; D., Altino; S., Sávio M.; CAMILO-JUNIOR, Celso G..
IVF/SPEA2: Estudo Preliminar de um Algoritmo Evolutivo Híbrido para Otimização Multiobjetivo. In: ESCOLA REGIONAL DE INFORMÁTICA DE GOIÁS (ERI-GO), 13. , 2025, Luziânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 341-344.
DOI: https://doi.org/10.5753/erigo.2025.16959.
