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A Set Based Newton Method for the Averaged Hausdorff Distance for Multi-Objective Reference Set Problems

1
Instituto Politécnico Nacional, Mexico City 07738, Mexico
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Departamento de Matemáticas, Pontificia Universidad Javeriana, Cra. 7 N. 40-62, Bogotá D.C. 111321, Colombia
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Department of Computer Science, TU Dortmund University, 44227 Dortmund, Germany
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Department of Computer Science, Cinvestav-IPN, Mexico City 07360, Mexico
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(10), 1822; https://doi.org/10.3390/math8101822
Received: 4 September 2020 / Revised: 2 October 2020 / Accepted: 11 October 2020 / Published: 17 October 2020
Multi-objective optimization problems (MOPs) naturally arise in many applications. Since for such problems one can expect an entire set of optimal solutions, a common task in set based multi-objective optimization is to compute N solutions along the Pareto set/front of a given MOP. In this work, we propose and discuss the set based Newton methods for the performance indicators Generational Distance (GD), Inverted Generational Distance (IGD), and the averaged Hausdorff distance Δp for reference set problems for unconstrained MOPs. The methods hence directly utilize the set based scalarization problems that are induced by these indicators and manipulate all N candidate solutions in each iteration. We demonstrate the applicability of the methods on several benchmark problems, and also show how the reference set approach can be used in a bootstrap manner to compute Pareto front approximations in certain cases. View Full-Text
Keywords: multi-objective optimization; Newton method; performance indicator Δp; generational distance; inverted generational distance; set based optimization multi-objective optimization; Newton method; performance indicator Δp; generational distance; inverted generational distance; set based optimization
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Uribe, L.; Bogoya, J.M.; Vargas, A.; Lara, A.; Rudolph, G.; Schütze, O. A Set Based Newton Method for the Averaged Hausdorff Distance for Multi-Objective Reference Set Problems. Mathematics 2020, 8, 1822.

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