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Dynamic Time-Linkage Evolutionary Optimization: Definitions and Potential Solutions

  • Chapter
Metaheuristics for Dynamic Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 433))

Abstract

Dynamic time-linkage optimization problems (DTPs) are special dynamic optimization problems (DOPs) where the current solutions chosen by the solver can influence how the problems might change in the future. Although DTPs are very common in real-world applications (e.g. online scheduling, online vehicle routing, and online optimal control problems), they have received very little attention from the evolutionary dynamic optimization (EDO) research community. Due to this lack of research there are still many characteristics that we do not fully know about DTPs. For example, how should we define and classify DTPs in detail; are there any characteristics of DTPs that we do not know; with these characteristics are DTPs still solvable; and what is the appropriate strategy to solve them. In this chapter these issues will be partially addressed. First, we will propose a detailed definition framework to help characterising DOPs and DTPs. Second, we will identify a new and challenging class of DTPs where it might not be possible to solve the problems using traditional methods. Third, an approach to solve this class of problems under certain circumstances will be suggested and experiments to verify the hypothesis will be carried out. Two test problems will be proposed to simulate the property of this new class of DTPs, and discussions of real-world applications will be introduced.

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Authors and Affiliations

  1. School of Engineering, Technology and Maritime Operations, Liverpool John Moores Univ., Liverpool, UK

    Trung Thanh Nguyen

  2. CERCIA, School of Computer Science, Univ. of Birmingham, Birmingham, UK

    Xin Yao

Authors
  1. Trung Thanh Nguyen
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  2. Xin Yao
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Correspondence to Trung Thanh Nguyen .

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Editors and Affiliations

  1. , E.T.S.I. Informática (3-2-12), Universidad de Málaga, Málaga, 29071, Spain

    Enrique Alba

  2. , LISSI, Université Paris-Est Créteil, avenue du Général de Gaulle 61, Créteil, 94010, France

    Amir Nakib

  3. , Laboratoire LiSSi, Université Paris-Est Créteil Val de Marn, avenue du Général de Gaulle 61, Créteil, 94010, France

    Patrick Siarry

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Nguyen, T.T., Yao, X. (2013). Dynamic Time-Linkage Evolutionary Optimization: Definitions and Potential Solutions. In: Alba, E., Nakib, A., Siarry, P. (eds) Metaheuristics for Dynamic Optimization. Studies in Computational Intelligence, vol 433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30665-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-30665-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30664-8

  • Online ISBN: 978-3-642-30665-5

  • eBook Packages: EngineeringEngineering (R0)

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