Theoretical advances in evolutionary dynamic optimization

Philipp ROHLFSHAGEN*, Per Kristian LEHRE, Xin YAO

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsBook ChapterResearchpeer-review

2 Citations (Scopus)


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. © 2013 Springer-Verlag Berlin Heidelberg.
Original languageEnglish
Title of host publicationEvolutionary Computation for Dynamic Optimization Problems
EditorsShengxiang YANG, Xin YAO
Number of pages20
ISBN (Electronic)9783642384165
ISBN (Print)9783642384158, 9783642448430
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503


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  • Evolutionary Computation for Dynamic Optimization Problems

    YANG, S. (ed.) & YAO, X. (ed.), 2013, Heidelberg: Springer. 470 p. (Studies in Computational Intelligence; vol. 490)

    Research output: Scholarly Books | Reports | Literary WorksBook (Editor)Researchpeer-review

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