The Pareto Tracer for General Inequality Constrained Multi-Objective Optimization Problems

Problems where several incommensurable objectives have to be optimized concurrently arise in many engineering and financial applications. Continuation methods for the treatment of such multi-objective optimization methods (MOPs) are very efficient if all objectives are continuous since in that case...

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Bibliographic Details
Published in:Mathematical and Computational Applications
Main Authors: Fernanda Beltrán, Oliver Cuate, Oliver Schütze
Format: Article
Language:English
Published: MDPI AG 2020-12-01
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Online Access:https://www.mdpi.com/2297-8747/25/4/80
Description
Summary:Problems where several incommensurable objectives have to be optimized concurrently arise in many engineering and financial applications. Continuation methods for the treatment of such multi-objective optimization methods (MOPs) are very efficient if all objectives are continuous since in that case one can expect that the solution set forms at least locally a manifold. Recently, the Pareto Tracer (PT) has been proposed, which is such a multi-objective continuation method. While the method works reliably for MOPs with box and equality constraints, no strategy has been proposed yet to adequately treat general inequalities, which we address in this work. We formulate the extension of the PT and present numerical results on some selected benchmark problems. The results indicate that the new method can indeed handle general MOPs, which greatly enhances its applicability.
ISSN:1300-686X
2297-8747