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Defining a Quality Measure Within Crossover: An Electric Bus Scheduling Case Study

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Artificial Evolution (EA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14091))

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Abstract

Genetic Algorithm (GA) crossover for permutation type problems is difficult due to the avoidance of vertex or value repetition. As a result extensive research into crossover operators has been undertaken with many variants developed. However, these crossover operators operate in a blind manner relying on the mechanics of survival of the fittest. A possible improvement is to introduce a quality measure into crossover enabling high quality edges to be utilised. This paper presents a crossover operator ER-Q that selects parental edges based upon their quality and applies this to an electric bus scheduling problem. Results demonstrate significant improvements in electric bus scheduling over alternative blind crossover operators. This paper also explores the definition of quality in terms of the electric bus scheduling problem noting that quality is difficult to quantify. A range of quality metrics are presented that can be used with differing effectiveness to optimally schedule electric buses.

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Acknowledgements

Supported by Innovate UK [grant no. 10007532] and City Science.

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Authors and Affiliations

  1. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK

    Darren M. Chitty & Ed Keedwell

Authors
  1. Darren M. Chitty
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  2. Ed Keedwell
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Corresponding author

Correspondence to Darren M. Chitty .

Editor information

Editors and Affiliations

  1. University of Bordeaux, Talence, France

    Pierrick Legrand

  2. University of Lille, Lille, France

    Arnaud Liefooghe

  3. University of Exeter, Exeter, UK

    Edward Keedwell

  4. Université de Haute-Alsace, Mulhouse, France

    Julien Lepagnot

  5. Université de Haute Alsace, Mulhouse, France

    Lhassane Idoumghar

  6. Ecole Polytechnique de Université de Tours, Tours, France

    Nicolas Monmarché

  7. INRA, Thirverval-Grignon, France

    Evelyne Lutton

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Chitty, D.M., Keedwell, E. (2023). Defining a Quality Measure Within Crossover: An Electric Bus Scheduling Case Study. In: Legrand, P., et al. Artificial Evolution. EA 2022. Lecture Notes in Computer Science, vol 14091. Springer, Cham. https://doi.org/10.1007/978-3-031-42616-2_6

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  • DOI: https://doi.org/10.1007/978-3-031-42616-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42615-5

  • Online ISBN: 978-3-031-42616-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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