Diagnostic assessment of the borg MOEA for many-objective product family design problems

David Hadka, Patrick M. Reed, Timothy W. Simpson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

46 Scopus citations

Abstract

The recently introduced Borg multiobjective evolutionary algorithm (MOEA) framework features auto-adaptive search that tailors itself to effectively explore different problem spaces. A key auto-adaptive feature of the Borg MOEA is the dynamic allocation of search across a suite of recombination and mutation operators. This study explores the application of the Borg MOEA on a real-world product family design problem: the severely constrained, ten objective General Aviation Aircraft (GAA) problem. The GAA problem represents a promising benchmark problem that strongly highlights the importance of using auto-adaptive search to discover how to exploit multiple recombination strategies cooperatively. The auto-adaptive behavior of the Borg MOEA is rigorously compared against its ancestor algorithm, the ε-MOEA, by employing global sensitivity analysis across each algorithm's feasible parameter ranges. This study provides the first Sobol' sensitivity analysis to determine the individual and interactive parameter sensitivities of MOEAs on a real-world many-objective problem.

Original languageEnglish (US)
Title of host publication2012 IEEE Congress on Evolutionary Computation, CEC 2012
DOIs
StatePublished - Oct 4 2012
Event2012 IEEE Congress on Evolutionary Computation, CEC 2012 - Brisbane, QLD, Australia
Duration: Jun 10 2012Jun 15 2012

Publication series

Name2012 IEEE Congress on Evolutionary Computation, CEC 2012

Other

Other2012 IEEE Congress on Evolutionary Computation, CEC 2012
CountryAustralia
CityBrisbane, QLD
Period6/10/126/15/12

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'Diagnostic assessment of the borg MOEA for many-objective product family design problems'. Together they form a unique fingerprint.

  • Cite this

    Hadka, D., Reed, P. M., & Simpson, T. W. (2012). Diagnostic assessment of the borg MOEA for many-objective product family design problems. In 2012 IEEE Congress on Evolutionary Computation, CEC 2012 [6256466] (2012 IEEE Congress on Evolutionary Computation, CEC 2012). https://doi.org/10.1109/CEC.2012.6256466