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)


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.


Fleet management systems Heterogeneous fleets Semantic recommendation systems 



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.


  1. 1.
  2. 2.
  3. 3.
  4. 4.
    Crainic, T.G., Laporte, G.: Fleet Management and Logistics. Springer, New York (2012). Scholar
  5. 5.
    Laporte, G., Gendreau, M., Potvin, J.Y., Semet, F.: Classical and modern heuristics for the vehicle routing problem. Int. Trans. Oper. Res. 7(4–5), 285–300 (2000)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Barthélemy, T., Rossi, A., Sevaux, M., Sörensen, K.: Metaheuristic approach for the clustered VRP. In: EU/MEeting: 10th Anniversary of the Metaheuristics Community-Université de Bretagne Sud, France (2010)Google Scholar
  7. 7.
    Krishnamurthy, N.N., Batta, R., Karwan, M.H.: Developing conflict-free routes for automated guided vehicles. Oper. Res. 41(6), 1077–1090 (1993)CrossRefGoogle Scholar
  8. 8.
    Langevin, A., Lauzon, D., Riopel, D.: Dispatching, routing, and scheduling of two automated guided vehicles in a flexible manufacturing system. Int. J. Flex. Manuf. Syst. 8(3), 247–262 (1996)CrossRefGoogle Scholar
  9. 9.
    Burt, C.N., Caccetta, L.: Equipment selection for surface mining: a review. Interfaces 44(2), 143–162 (2014)CrossRefGoogle Scholar
  10. 10.
    El-Moslmani, K., Alkass, S., Al-Hussein, M.: A computer module for multi-loaders-multi-trucks fleet selection for earthmoving projects. In: Proceedings of the Canadian Society for Civil Engineering Annual Conference, GE-107, Montréal (2002)Google Scholar
  11. 11.
    Burt, C., Caccetta, L., Welgama, P., Fouché, L.: Equipment selection with heterogeneous fleets for multiple-period schedules. J. Oper. Res. Soc. 62(8), 1498–1509 (2011)CrossRefGoogle Scholar
  12. 12.
    Aykul, H., Yalcin, E., Ediz, I.G., Dixon-Hardy, D.W., Akcakoca, H.: Equipment selection for high selective excavation surface coal mining. J. S. Afr. Inst. Min. Metall. 107(3), 195 (2007)Google Scholar
  13. 13.
    Colombo-Mendoza, L.O., Valencia-García, R., Rodríguez-González, A., Alor-Hernández, G., Samper-Zapater, J.J.: RecomMetz: a context-aware knowledge-based mobile recommender system for movie showtimes. Expert Syst. Appl. 42(3), 1202–1222 (2015)CrossRefGoogle Scholar
  14. 14.
    Rodríguez-García, M.Á., Colombo-Mendoza, L.O., Valencia-García, R., Lopez-Lorca, Antonio A., Beydoun, G.: Ontology-based music recommender system. In: Omatu, S., Malluhi, Q.M., Gonzalez, S.R., Bocewicz, G., Bucciarelli, E., Giulioni, G., Iqba, F. (eds.) Distributed Computing and Artificial Intelligence, 12th International Conference. AISC, vol. 373, pp. 39–46. Springer, Cham (2015). Scholar
  15. 15.
    Feld, M., Müller, C.: The automotive ontology: managing knowledge inside the vehicle and sharing it between cars. In: Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications, pp. 79–86 (2011)Google Scholar
  16. 16.
    Sun, J., Wu, Z.H., Pan, G.: Context-aware smart car: from model to prototype. J. Zhejiang Univ. Sci. A 10(7), 1049–1059 (2009)CrossRefGoogle Scholar
  17. 17.
    Zhao, L., Ichise, R., Yoshikawa, T., Naito, T., Kakinami, T., Sasaki, Y.: Ontology-based decision making on uncontrolled intersections and narrow roads. In: IEEE IV Intelligent Vehicles Symposium, pp. 83–88 (2015)Google Scholar
  18. 18.
    Mizoguchi, R.: Part 1: introduction to ontological engineering. New Gener. Comput. 21(4), 365–384 (2003)CrossRefGoogle Scholar
  19. 19.
    Ramchurn, S.D., Sierra, C., Godó, L., Jennings, N.R.: A computational trust model for multi-agent interactions based on confidence and reputation. In: Proceedings of 6th International Workshop of Deception, Fraud and Trust in Agent Societies, pp. 69–75 (2003)Google Scholar
  20. 20.
    Hermoso, R., Billhardt, H., Ossowski, S.: Integrating trust in virtual organisations. In: Noriega, P., Vázquez-Salceda, J., Boella, G., Boissier, O., Dignum, V., Fornara, N., Matson, E. (eds.) COIN -2006. LNCS (LNAI), vol. 4386, pp. 19–31. Springer, Heidelberg (2007). Scholar
  21. 21.
    Billhardt, H., Fernández, A., Lujak, M., Ossowski, S., Julián, V., de Paz, J.F., Hernández, J.: Coordinating open fleets. A taxi assignment example. AI Commun. 30(1), 37–52 (2017)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Universidad Rey Juan CarlosMadridSpain

Personalised recommendations