A new multiobjective genetic programming for extraction of design information from non-dominated solutions

Tomoaki Tatsukawa, Taku Nonomura, Akira Oyama, Kozo Fujii

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

2 Citations (Scopus)

Abstract

We propose a new type of multi-objective genetic programming (MOGP) for multi-objective design exploration (MODE). The characteristic of the new MOGP is the simultaneous symbolic regression to multiple objective functions using correlation coefficients. This methodology is applied to non-dominated solutions of the multi-objective design optimization problem to extract information between objective functions and design parameters. The result of MOGP is symbolic equations that are highly correlated to each objective function through a single GP run. These equations are also highly correlated to several objective functions. The results indicate that the proposed MOGP is capable of finding new design parameters more closely related to the objective functions than the original design parameters. The proposed MOGP is applied to the test problem and the practical design problem to evaluate the capability.

Original languageEnglish
Title of host publicationEvolutionary Multi-Criterion Optimization - 7th International Conference, EMO 2013, Proceedings
Pages528-542
Number of pages15
DOIs
Publication statusPublished - 2013 Apr 3
Externally publishedYes
Event7th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2013 - Sheffield, United Kingdom
Duration: 2013 Mar 192013 Mar 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7811 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2013
Country/TerritoryUnited Kingdom
CitySheffield
Period13/3/1913/3/22

Keywords

  • CFD
  • Multi-Objective Design Explolation
  • Multi-Objective Genetic Programming
  • NSGA-II

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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