Sustainable Smart Cities: Optimization of Demand Responsive Transport by Using Data Science Tools

  • Naila FaresEmail author
  • Abdelouahid Lyahyaoui
  • Abdelfettah Sedqui
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1104)


Faced with the widely demonstrated disadvantages of individual transport, demand responsive transport (DRT) is the solution chosen by companies to ensure the transportation of its employees, however, the growth of industrial activities generates great difficulty in managing this model of transport. This research can be applied to very broad areas, in our case we aim to apply it to the city of Tangier. The objective is to minimize the collection routes of transport vehicles. In this article, we propose an optimization approach in data mining, by using clustering, multidimensional positioning (MDS), as well as a wide range of graph theory techniques. It is a vital element, of the strategies developed within the smart cities framework. We test our approach by a random data set of 40 employee pick-up points. An optimal cycle is founded, optimizing the collection.


Optimization Transport Demand responsive transport Smart cities 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Naila Fares
    • 1
    • 2
    Email author
  • Abdelouahid Lyahyaoui
    • 1
  • Abdelfettah Sedqui
    • 1
  1. 1.Ecole Nationale des Sciences Appliquées de Tanger (ENSAT)TangierMorocco
  2. 2.Ecole Mohammadia d’Ingénieurs (EMI)RabatMorocco

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