Theoretical advances in evolutionary dynamic optimization

Research output: Chapter in Book/Report/Conference proceedingChapter

Authors

Colleges, School and Institutes

External organisations

  • University of Birmingham
  • University of Nottingham

Abstract

The field of evolutionary dynamic optimization is concerned with the study and application of evolutionary algorithms to dynamic optimization problems: a significant number of new algorithms have been proposed in recent years that are designed specifically to overcome the limitations faced by traditional algorithms in the dynamic domain. Subsequently, a wealth of empirical studies have been published that evaluate the performance of these algorithms on a variety of benchmark problems. However, very few theoretical results have been obtained during this time. This relative lack of theoretical findings makes it difficult to fully assess the strengths and weaknesses of the individual algorithms. In this chapter we provide a review of theoretical advances in evolutionary dynamic optimization. In particular, we argue the importance of theoretical results, highlight the challenges faced by theoreticians and summarise the work that has been done to date. We subsequently identify relevant directions for future research.

Details

Original languageEnglish
Title of host publicationEvolutionary Computation for Dynamic Optimization Problems
Publication statusPublished - 2013

Publication series

NameStudies in Computational Intelligence
Volume490
ISSN (Print)1860949X

ASJC Scopus subject areas