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Provider Recommendation in Heterogeneous Transportation Fleets

  • Miguel Ángel Rodríguez-García
  • Alberto Fernández
  • Holger Billhardt
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 887)

Abstract

Nowadays, transportation is a critical sector of our lives, not only for the movement of people, but also to be capable to move goods around the world. Although providing such services can be seen as a very tiny problem in our society, behind it, there is a complex sector that requires sophisticated models and specific software to analyse a vast amount of information coming from different sources in order to provide a sustainable and efficient service. Given such a complex field, various issues have come up like the search of optimised routes, efficient assignment of vehicles, reduction of gas emissions, cost optimization problems, etc. In most cases, the provided approaches are focused on addressing the optimization problem considering fleets with identical features. In this work, we present HVSRec, a heterogeneous fleet semantic recommender system that integrates mechanisms to manage vehicles of different nature and characteristics efficiently. The platform is aimed to connect customers that request a transportation of a certain good with drivers that are offering transportation services with their own vehicle.

Keywords

Fleet management systems Heterogeneous fleets Semantic recommendation systems 

Notes

Acknowledgments

Work partially supported by the Autonomous Region of Madrid (grant “MOSI-AGIL-CM” (S2013/ICE-3019) co-funded by EU Structural Funds FSE and FEDER), project “SURF” (TIN2015-65515-C4-4-R (MINECO/FEDER)) funded by the Spanish Ministry of Economy and Competitiveness, and through the Excellence Research Group GES2ME (Ref. 30VCPIGI05) co-funded by URJC and Santander Bank.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Universidad Rey Juan CarlosMadridSpain

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