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Modifying Colourings Between Time-Steps to Tackle Changes in Dynamic Random Graphs

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Evolutionary Computation in Combinatorial Optimization (EvoCOP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9595))

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Abstract

Many real world operational research problems can be formulated as graph colouring problems. Algorithms for this problem usually operate under the assumption that the size and constraints of a problem are fixed, allowing us to model the problem using a static graph. For many problems however, this is not the case and it would be more appropriate to model such problems using dynamic graphs. In this paper we will explore whether feasible colourings for one graph at time-step t can be modified into a colouring for a similar graph at time-step \(t+1\) in some beneficial manner.

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Notes

  1. 1.

    All algorithms were programmed in C++ and executed on a 3.3 GHZ Windows 7 PC with an Intel Core i3-2120 processor and 8 GB RAM.

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Author information

Authors and Affiliations

  1. School of Mathematics, Cardiff University, Cardiff, CF24 4AG, UK

    Bradley Hardy, Rhyd Lewis & Jonathan Thompson

Authors
  1. Bradley Hardy
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  2. Rhyd Lewis
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  3. Jonathan Thompson
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Corresponding author

Correspondence to Bradley Hardy .

Editor information

Editors and Affiliations

  1. University of Málaga, Málaga, Spain

    Francisco Chicano

  2. Austrian Insttitute of Technology, Vienna, Austria

    Bin Hu

  3. University of Granada, Granada, Spain

    Pablo García-Sánchez

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© 2016 Springer International Publishing Switzerland

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Hardy, B., Lewis, R., Thompson, J. (2016). Modifying Colourings Between Time-Steps to Tackle Changes in Dynamic Random Graphs. In: Chicano, F., Hu, B., García-Sánchez, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2016. Lecture Notes in Computer Science(), vol 9595. Springer, Cham. https://doi.org/10.1007/978-3-319-30698-8_13

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  • DOI: https://doi.org/10.1007/978-3-319-30698-8_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30697-1

  • Online ISBN: 978-3-319-30698-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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