Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems

Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We have recently presented SAFE - Solution And Fitness Evolution - a commensalistic coevolutionary algorithm that maintains two coevolving populations: a population of candidate solutions and a population of candidate objective functions. We showed that SAFE was successful at evolving solutions within a robotic maze domain. Herein we present an investigation of SAFE's adaptation and application to multiobjective problems, wherein candidate objective functions explore different weightings of each objective. Though preliminary, the results suggest that SAFE, and the concept of coevolving solutions and objective functions, can identify a similar set of optimal multiobjective solutions without explicitly employing a Pareto front for fitness calculation and parent selection. These findings support our hypothesis that the SAFE algorithm concept can not only solve complex problems, but can adapt to the challenge of problems with multiple objectives.

Original languageAmerican English
Title of host publication2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
Pages1868-1874
Number of pages7
ISBN (Electronic)9781728121536
DOIs
StatePublished - 1 Jun 2019
Event2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, New Zealand
Duration: 10 Jun 201913 Jun 2019

Publication series

Name2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

Conference

Conference2019 IEEE Congress on Evolutionary Computation, CEC 2019
Country/TerritoryNew Zealand
CityWellington
Period10/06/1913/06/19

Keywords

  • coevolution
  • evolutionary computation
  • multiobjective optimization
  • novelty search
  • objective function

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Modelling and Simulation

Fingerprint

Dive into the research topics of 'Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems'. Together they form a unique fingerprint.

Cite this