Document Open Access Logo

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

Authors Enrico Rigoni, Silvia Poles



PDF
Thumbnail PDF

File

DagSemProc.04461.15.pdf
  • Filesize: 0.72 MB
  • 22 pages

Document Identifiers

Author Details

Enrico Rigoni
Silvia Poles

Cite AsGet BibTex

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)
https://doi.org/10.4230/DagSemProc.04461.15

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 NBI´s convergence. In order to overcome this problem, a hybridization technique coupled with a partitioning method is proposed.
Keywords
  • Genetic Algorithms
  • Normal-Boundary Intersection
  • Designs optimizations

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail