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Evolutionary Dynamic Optimization: Challenges and Perspectives

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Evolutionary Computation for Dynamic Optimization Problems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 490))

Abstract

The field of evolutionary dynamic optimization is concerned with the study and application of evolutionary algorithms to dynamic optimization problems. In this chapter we highlight some of the challenges associated with the time-variant nature of these problems.We focus particularly on the different problem definitions that have been proposed, the modelling of dynamic optimization problems in terms of benchmark suites and the way the performance of an algorithm is assessed. Amid significant developments in the last decade, several practitioners have highlighted shortcomings with all of these fundamental issues. In this chapter we review the work done in each of these areas, evaluate the criticism and subsequently identify some perspectives for the future of the field.

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Authors and Affiliations

  1. Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA), School of Computer Science, University of Birmingham, Birmingham, B15 2TT, U.K.

    Philipp Rohlfshagen & Xin Yao

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  1. Philipp Rohlfshagen
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  2. Xin Yao
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Correspondence to Philipp Rohlfshagen .

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Editors and Affiliations

  1. , School of Computer Science and Informati, De Montfort University, The Gateway, Leicester, LE1 9BH, United Kingdom

    Shengxiang Yang

  2. , School of Computer Science, University of Birmingham, Birmingham, B15 2TT, United Kingdom

    Xin Yao

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Rohlfshagen, P., Yao, X. (2013). Evolutionary Dynamic Optimization: Challenges and Perspectives. In: Yang, S., Yao, X. (eds) Evolutionary Computation for Dynamic Optimization Problems. Studies in Computational Intelligence, vol 490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38416-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-38416-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38415-8

  • Online ISBN: 978-3-642-38416-5

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