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NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations

Authors: Enrico Rigoni and Silvia Poles

Published in: Dagstuhl Seminar Proceedings, Volume 4461, Practical Approaches to Multi-Objective Optimization (2005)

Abstract

The NBI-NLPQLP optimization method is tested on several multi-objective optimization problems. Its performance is compared to that of MOGA-II: since NBI-NLPQLP is based on the classical gradient-based NLPQLP, it is fast and accurate, but not as robust, in comparison with the genetic algorithm. Furthermore a discontinuous Pareto frontier can give rise to problems in the NBIÃ‚Â´s convergence. In order to overcome this problem, a hybridization technique coupled with a partitioning method is proposed.

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Enrico Rigoni and Silvia Poles. NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{rigoni_et_al:DagSemProc.04461.15,
  author =	{Rigoni, Enrico and Poles, Silvia},
  title =	{{NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--22},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4461},
  editor =	{J\"{u}rgen Branke and Kalyanmoy Deb and Kaisa Miettinen and Ralph E. Steuer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.04461.15},
  URN =		{urn:nbn:de:0030-drops-2728},
  doi =		{10.4230/DagSemProc.04461.15},
  annote =	{Keywords: Genetic Algorithms, Normal-Boundary Intersection, Designs optimizations}
}

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NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations

Abstract

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