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Soft Computing

, Volume 22, Issue 22, pp 7407–7421 | Cite as

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

  • Daniel Jato-Espino
  • Irune Indacoechea-Vega
  • László Gáspár
  • Daniel Castro-Fresno
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Abstract

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project “DURABROADS” (No. 605404).

Keywords

AHP Fuzzy logic Monte Carlo methods Multi-criteria decision-making Road management TOPSIS 

Notes

Acknowledgements

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404. This paper reflects only the authors’ views, and the Community is not liable for any use that may be made of the information contained therein. The authors wish to thank the participants of the DURABROADS Work Package 2 (ACCIONA Infraestructuras S.A., European Union Road Federation and Inzenierbuve SIA) for their inestimable contribution to the research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.GITECO Research GroupUniversidad de CantabriaSantanderSpain
  2. 2.KTI (Institute for Transport Sciences)BudapestHungary

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