Abstract
Freight transport optimization, long based solely on an economic approach, happen today through the integration of environmental and/or social concerns, in line with the objectives of sustainable development. In the case of Small and Very Small Enterprises, these objectives cannot be reached individually, and these companies have to join their efforts to find collective solutions. Therefore, the Fleet Size and Mix Vehicle Routing Problem (FSMVRP) was adapted to take into account social objectives, and results are compared to Vehicle Routing Problem with homogeneous fleet. An exact mathematical formulation of the extended problem was developed. Computational experiments for the problem formulation are performed using CPLEX and give a solution of a small instance to illustrate the problem. The model is tested on a case study of optimal parcel pickup, from many manufacturers to a common depot in the agri-food sector.
Chapter PDF
Similar content being viewed by others
Keywords
References
Conservatoire National des Arts et Métiers (CNAM): Enquête Nationale: La logistique dans les PME-PMI de l’agroalimentaire, synthèse des résultats. Chaire de Logistique, Transport, Tourisme (2007)
Pôle Agroalimentaire Loire: Organisation logistique du secteur agroalimentaire dans la Loire (2011)
Creazza, A., Dallari, F., Rossi, T.: Applying an integrated logistics network design and optimisation model: the Pirelli Tyre case. International Journal of Production Research 50, 3021–3038 (2012)
Moutaoukil, A., Derrouiche, R., Neubert, G.: Modeling a Logistics Pooling Strategy for Agri-Food SMEs. In: Camarinha-Matos, L.M., Scherer, R.J. (eds.) PRO-VE 2013. IFIP AICT, vol. 408, pp. 621–630. Springer, Heidelberg (2013)
Hoff, A., Andersson, H., Christiansen, M., Hasle, G., Løkketangen, A.: Industrial aspects and literature survey: Fleet composition and routing. Computers & Operations Research 37, 2041–2061 (2010)
Pasha, U., Hoff, A., Løkketangen, A.: The Shrinking and Expanding Heuristic for the Fleet Size and Mix Vehicle Routing Problem, pp. 6–13. Scientific Letters, University of Zilina (2013)
Hasle, G., Kloster, O.: Industrial Vehicle Routing. In: Quak, E. (ed.) Geometric Modelling, Numerical Simulation, and Optimization, pp. 397–435. Springer, Heidelberg (2007)
Taillard, E.D.: A heuristic column generation method for the heterogeneous fleet Vehicle Routing Problem. RAIRO - Operations Research 33, 1–14 (1999)
Bräysy, O., Dullaert, W., Hasle, G., Mester, D., Gendreau, M.: An Effective Multirestart Deterministic Annealing Metaheuristic for the Fleet Size and Mix Vehicle-Routing Problem with Time Windows. Transportation Science 42, 371–386 (2008)
Tarantilis, C.D., Kiranoudis, C.T., Vassiliadis, V.S.: A threshold accepting metaheuristic for the heterogeneous fixed fleet VRP. European Journal of Operational Research 152, 148–158 (2004)
Semet, F.: A two-phase algorithm for the partial accessibility constrained vehicle routing problem. Ann. Oper. Res. 61, 45–65 (1995)
Kopfer, H.W., Schönberger, J., Kopfer, H.: Reducing greenhouse gas emissions of a heterogeneous vehicle fleet. Flex. Serv. Manuf. J. 26, 221–248 (2014)
Jancovici, M.: Temis - Bilan carbone. Guide des facteurs d’émissions - Calcul des facteurs d’émissions et sources bibliographiques utilisées (Monographie). ADEME France, Paris, France (2007)
Hickman, J., Hassel, D., Joumard, R., Samaras, Z., Sorenson, S.: Methodology for calculating transport emissions and energy consumption (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 IFIP International Federation for Information Processing
About this paper
Cite this paper
Derrouiche, R., Moutaoukil, A., Neubert, G. (2014). Integration of Social Concerns in Collaborative Logistics and Transportation Networks. In: Camarinha-Matos, L.M., Afsarmanesh, H. (eds) Collaborative Systems for Smart Networked Environments. PRO-VE 2014. IFIP Advances in Information and Communication Technology, vol 434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44745-1_72
Download citation
DOI: https://doi.org/10.1007/978-3-662-44745-1_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-44744-4
Online ISBN: 978-3-662-44745-1
eBook Packages: Computer ScienceComputer Science (R0)