PBI-BFS-MaOA: A Many-Objective Evolutionary Algorithm with PBI-Based Boundary-Front Selection

Reference-guided many-objective evolutionary al-gorithms often lose selection pressure when Pareto dominance becomes scarce and the final accepted front must be truncated. We propose PBI-BFS-MaOA, a many-objective evolutionary algorithm that preserves Pareto ranking for feasible solutions and modifi...

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-д хэвлэсэн:	Latin-American Journal of Computing (LAJC)
Үндсэн зохиолчид:	Thiago Santos, Sebastiao Xavier
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	Escuela Politécnica Nacional 2026
Нөхцлүүд:	Computación Many penalty reference directions objective optimization environmental selection
Онлайн хандалт:	https://www.redalyc.org/articulo.oa?id=823985609004 https://www.redalyc.org/journal/8239/823985609004/ https://www.redalyc.org/journal/8239/823985609004/html/ https://www.redalyc.org/journal/8239/823985609004/823985609004.epub https://www.redalyc.org/journal/8239/823985609004/movil
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