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Dimensionality Reduction Approach for Many-Objective Vehicle Routing Problem with Demand Responsive Transport

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Evolutionary Multi-Criterion Optimization (EMO 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10173))

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Abstract

Demand Responsive Transport (DRT) systems emanate as a substitute to face the problem of volatile, or even inconstant, demand, occurring in popular urban transport systems. This paper is focused in the Vehicle Routing Problem with Demand Responsive Transport (VRPDRT), a type of transport which enables passengers to be taken to their destination, as a shared service, trying to minimize the company costs and offer a quality service taking passengers on their needs. A many-objective approach is applied in VRPDRT in which seven different objective functions are used. To solve the problem through traditional multi-objective algorithms, the work proposes the usage of cluster analysis to perform the dimensionaly reduction task. The seven functions are then aggregated resulting in a bi-objective formulation and the algorithms NSGA-II and SPEA 2 are used to solve the problem. The results show that the algorithms achieve statistically different results and NSGA-II reaches a greater number of non-dominated solutions when compared to SPEA 2. Furthermore, the results are compared to an approach proposed in literature that uses another way to reduce the dimensionality of the problem in a two-objective formulation and the cluster analysis procedure is proven to be a competitive methodology in that problem. It is possbile to say that the behavior of the algorithm is modified by the way the dimensionality reduction of the problem is made.

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Acknowledgments

The authors would like to thank the Brazilian funding agencies, CNPq, CAPES and Fapemig for financial support.

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Authors and Affiliations

  1. Programa de Pós-Graduação em Modelagem Matemática e Computacional CEFET, Belo Horizonte, Minas Gerais, Brazil

    Renan Mendes

  2. Departamento de Computação, CEFET, Belo Horizonte, Minas Gerais, Brazil

    Elizabeth Wanner, Flávio Martins & João Sarubbi

Authors
  1. Renan Mendes
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  2. Elizabeth Wanner
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  3. Flávio Martins
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  4. João Sarubbi
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Corresponding author

Correspondence to Renan Mendes .

Editor information

Editors and Affiliations

  1. University of Münster, Münster, Germany

    Heike Trautmann

  2. TU Dortmund University, Dortmund, Germany

    Günter Rudolph

  3. University of Wuppertal, Wuppertal, Germany

    Kathrin Klamroth

  4. CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze

  5. Clemson University, Clemson, South Carolina, USA

    Margaret Wiecek

  6. University of Surrey, Guildford, United Kingdom

    Yaochu Jin

  7. University of Münster, Münster, Germany

    Christian Grimme

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Mendes, R., Wanner, E., Martins, F., Sarubbi, J. (2017). Dimensionality Reduction Approach for Many-Objective Vehicle Routing Problem with Demand Responsive Transport. In: Trautmann, H., et al. Evolutionary Multi-Criterion Optimization. EMO 2017. Lecture Notes in Computer Science(), vol 10173. Springer, Cham. https://doi.org/10.1007/978-3-319-54157-0_30

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  • DOI: https://doi.org/10.1007/978-3-319-54157-0_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54156-3

  • Online ISBN: 978-3-319-54157-0

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