In this paper an extension of Generalized Differential Evolution for constrained multi-objective (Pareto-)optimization is proposed. The proposed extension adds a mechanism for maintaining extent and distribution of the obtained non-dominated solutions approximating a Pareto front. The proposed extension is tested with a set of five benchmark multi-objective test problems and results are numerically compared to known global Pareto fronts and to results obtained with the elitist Non-Dominated Sorting Genetic Algorithm and Generalized Differential Evolution. Results show that the extension improves extent and distribution of solutions of Generalized Differential Evolution. © Springer-Verlag 2004.
CITATION STYLE
Kukkonen, S., & Lampinen, J. (2004). An extension of generalized differential evolution for multi-objective optimization with constraints. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3242, 752–761. https://doi.org/10.1007/978-3-540-30217-9_76
Mendeley helps you to discover research relevant for your work.