Skip to main content
SpringerLink
Log in

Dynamic Time-Linkage Problems Revisited

  • Conference paper
Applications of Evolutionary Computing (EvoWorkshops 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5484))

Included in the following conference series:

Abstract

Dynamic time-linkage problems (DTPs) are common types of dynamic optimization problems where ”decisions that are made now ... may influence the maximum score that can be obtained in the future” [3]. This paper contributes to understanding the questions of what are the unknown characteristic of DTPs and how to characterize DTPs. Firstly, based on existing definitions we will introduce a more detailed definition to help characterize DTPs. Secondly, although it is believed that DTPs can be solved to optimality with a perfect prediction method to predict function values [3] [4], in this paper we will discuss a new class of DTPs where even with such a perfect prediction method algorithms might still be deceived and hence will not be able to get the optimal results. We will also propose a benchmark problem to study that particular type of time-linkage problems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bäck, T.: On the behavior of evolutionary algorithms in dynamic environments. In: Proc. of the IEEE Intl. Conf. on Evolutionary Computation, pp. 446–451 (1998)

    Google Scholar 

  2. Bäck, T.: Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford Univ. Press, Oxford (1996)

    MATH  Google Scholar 

  3. Bosman, P.A.N.: Learning, anticipation and time-deception in evolutionary online dynamic optimization. In: Proc. of the GECCO 2005 Conf., pp. 39–47 (2005)

    Google Scholar 

  4. Bosman, P.A.N., Poutré, H.L.: Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case. In: GECCO 2007: Proc. of the 9th Conf. on Genetic and Evoluntionary Computation, pp. 1165–1172. ACM, New York (2007)

    Chapter  Google Scholar 

  5. Bosman, P.A.N.: Learning and Anticipation in Online Dynamic Optimization. In: Yang, S., Ong, Y.S., Jin, Y. (eds.) Evolutionary Computation in Dynamic and Uncertain Environments, pp. 129–152. Springer, Berlin (2007)

    Chapter  Google Scholar 

  6. Branke, J., Mattfeld, D.: Anticipation in dynamic optimization: The scheduling case. In: Deb, K., et al. (eds.) PPSN 2000. LNCS, vol. 1917, pp. 253–262. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  7. Dorfman, R.: An Economic Interpretation of Optimal Control Theory. American Economic Review 59(5), 817–831 (1969)

    Google Scholar 

  8. van Hemert, J.I., La Poutre, J.A.: Dynamic routing problems with fruitful regions: Models and evolutionary computation. In: Yao, X., et al. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 692–701. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  9. Li, C., Yang, S., Nguyen, T.T., Yu, E.L., Yao, X., Jin, Y., Beyer, H.-G., Suganthan, P.N.: Benchmark Generator for CEC 2009 Competition on Dynamic Optimization, Technical report, University of Leicester and University of Birmingham, UK (2008), http://www.cs.le.ac.uk/people/syang/ECiDUE/DBG.tar.gz

  10. Morrison, R.W.: Designing Evolutionary Algorithms for Dynamic Environments. Springer, Berlin (2004)

    Book  MATH  Google Scholar 

  11. Nguyen, T.T.: A benchmark for dynamic time-linkage problems, Technical Report, School of Computer Science, University of Birmingham (2009)

    Google Scholar 

  12. Rohlfshagen, P., Yao, X.: Attributes of combinatorial optimisation. In: Proc. of the 7th Int. Conf. on Simulated Evolutionand Learning, pp. 442–451. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  13. Sistu, P.B., Gopinath, R.S., Bequette, B.W.: Computational issues in nonlinear predictive control. Comput. Chem. Eng. 17, 361–367 (1993)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Trung Thanh Nguyen & Xin Yao

Authors
  1. Trung Thanh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Animal Production Epidemiology and Ecology, University of Torino, Via Leonardo da Vinci 44, 10095, Grugliasco, Italy

    Mario Giacobini

  2. Quinn School of Business, Belfield, University College Dublin, Dublin 4, Ireland

    Anthony Brabazon

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. Dalla Molle Institute for Artificial Intelligence (IDSIA), Gallelria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  5. School of Engineering and Applied Science,Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Complex Adaptive Systems Group, Instituto Tecnológico de Informática, Ciudad PolitŽcnica de la Innovacin, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna Isabel Esparcia-Alcázar

  7. Next Generation Itelligent Networks Research Center (nexGIN RC), National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan

    Muddassar Farooq

  8. Faculty of Economics and Social Sciences, Helmut-Schmidt-University, Holstenhofweg 85, 22043, Hamburg, Germany

    Andreas Fink

  9. Department of Informatics Engineering, Polo II - Pinhal de Marrocos, University of Coimbra, 3030 - 290, Coimbra, Portugal

    Penousal Machado

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nguyen, T.T., Yao, X. (2009). Dynamic Time-Linkage Problems Revisited. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_83

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01129-0_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01128-3

  • Online ISBN: 978-3-642-01129-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation