Towards E(lectric)- urban freight: first promising steps in the electric vehicle revolution

Innovative logistics service providers are currently looking for possibilities to introduce electric vehicles for goods distribution. As electrical vehicles still suffer from a limited operation range, the logistical process faces important challenges. In this research we advise on the composition of the electrical vehicle fleet and on the configuration of the service network, to achieve a successful implementation of electric vehicles in the innercity of Amsterdam. Additional question in our research is whether the CO2 emission reduces at all or might even increase due to an increase of tripkilometres as a consequence of mileage constraints by the batteries. The aim of the implementation of the research is to determine the ideal fleet to transport a known demand of cargo, located at a central depot, to a known set of recipients using vehicles of varying types. The problem can be classified as a Fleet Size and Mix Vehicle Routing Problem (FSMVRP). In addition to the regular constraints that apply to the regular FSMVRP, in our case also time windows apply to the cargo that needs to be transported (FSMVRPTW). The operation range of the vehicles is constrained by the battery capacity. We suggest modifications to existing formulations of the FSMVRPTW to make it suitable for the application on cases with electrical vehicles. We apply the model to create an optimal fleet configuration and the service routes. In our research case of the Cargohopper in Amsterdam, the performance of alternative fleet compositions is determined for a variety of scenarios, to assess their robustness. The main uncertainties addressed in the scenarios are the cargo composition, the operation range of the vehicles and their operation speed. Based on our research findings in Amsterdam we conclude that the current generation of electric vehicles as a part of urban consolidation concept have the ability to perform urban freight transport efficiently (19% reduction in vehicle kilometres) and meanwhile have the capability to improve air quality and reduce CO2-emissions by 90%, and reduce noise nuisance in the inner cities of our (future) towns.

[1]  L. Dablanc Goods transport in large European cities: Difficult to organize, difficult to modernize , 2007 .

[2]  F.-H. Liu,et al.  The fleet size and mix vehicle routing problem with time windows , 1999, J. Oper. Res. Soc..

[3]  Marielle Christiansen,et al.  Industrial aspects and literature survey: Fleet composition and routing , 2010, Comput. Oper. Res..

[4]  Guido Perboli,et al.  The Influence of Time Windows on the Costs of Urban Freight Distribution Services in City Logistics Applications , 2012 .

[5]  Julian Allen,et al.  Urban freight consolidation centres: final report , 2005 .

[6]  T. Crainic,et al.  ADVANCED FREIGHT TRANSPORTATION SYSTEMS FOR CONGESTED URBAN AREAS , 2004 .

[7]  Eiichi Taniguchi,et al.  An Analysis of Exact VRPTW Solutions on ITS Data-based Logistics Instances , 2012, Int. J. Intell. Transp. Syst. Res..

[8]  Michel Bierlaire,et al.  European Transport \ Trasporti Europei , 2005 .

[9]  Bruce L. Golden,et al.  The fleet size and mix vehicle routing problem , 1984, Comput. Oper. Res..

[10]  Said Salhi,et al.  Incorporating vehicle routing into the vehicle fleet composition problem , 1993 .

[11]  Nikolaos Geroliminis,et al.  A review of green logistics schemes used in cities around the world , 2005 .

[12]  Michael Browne,et al.  Urban Freight Consolidation Centers , 2014 .

[13]  Luis Onieva,et al.  Solutions applicable by local administrations for urban logistics , 2005 .

[14]  Michel Gendreau,et al.  Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms , 2005, Transp. Sci..

[15]  H. J. Quak,et al.  Delivering Goods in Urban Areas: How to Deal with Urban Policy Restrictions and the Environment , 2009, Transp. Sci..

[16]  Michel Gendreau,et al.  An Effective Multirestart Deterministic Annealing Metaheuristic for the Fleet Size and Mix Vehicle-Routing Problem with Time Windows , 2008, Transp. Sci..

[17]  Frank Harary,et al.  Graph Theory , 2016 .

[18]  E Taniguchi,et al.  NEW CO-OPERATIVE SYSTEM USING ELECTRIC VANS FOR URBAN FREIGHT TRANSPORT , 2000 .

[19]  Eiichi Taniguchi,et al.  Vehicle Routing and Scheduling , 2001 .

[20]  H. Quak Sustainability of Urban Freight Transport: Retail Distribution and Local Regulations in Cities , 2008 .

[21]  Goos Kant,et al.  Coca-Cola Enterprises Optimizes Vehicle Routes for Efficient Product Delivery , 2008, Interfaces.

[22]  S. Salhi,et al.  Local Search Strategies for the Vehicle Fleet Mix Problem , 1996 .

[23]  Jacques Leonardi,et al.  Evaluating the use of an urban consolidation centre and electric vehicles in central London , 2011 .

[24]  Thomas L. Magnanti,et al.  Applied Mathematical Programming , 1977 .

[25]  Miguel A. Figliozzi,et al.  A Methodology to Evaluate the Competitiveness of Electric Delivery Trucks , 2013 .

[26]  Miguel A. Figliozzi,et al.  The Recharging Vehicle Routing Problem , 2011 .

[27]  P. Bhatia,et al.  The greenhouse gas protocol : a corporate accounting and reporting standard , 2001 .

[28]  Jesús Muñuzuri,et al.  How efficient is city logistics? Estimating ecological footprints for urban freight deliveries , 2010 .

[29]  Jesús Muñuzuri,et al.  New challenges for urban consolidation centres: A case study in The Hague , 2010 .

[30]  H. Quak,et al.  Exploring Retailers' Sensitivity to Local Sustainability Policies , 2005 .

[31]  Michel Gendreau,et al.  Vehicle Routing Problem with Time Windows, Part II: Metaheuristics , 2005, Transp. Sci..

[32]  Albert P. M. Wagelmans,et al.  A savings based method for real-life vehicle routing problems , 1999, J. Oper. Res. Soc..

[33]  Marius M. Solomon,et al.  Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints , 1987, Oper. Res..

[34]  Jean-Marie Boussier,et al.  Simulation of goods delivery process , 2011 .

[35]  Gerrit K. Janssens,et al.  New heuristics for the Fleet Size and Mix Vehicle Routing Problem with Time Windows , 2002, J. Oper. Res. Soc..

[36]  Miguel A. Figliozzi,et al.  An economic and technological analysis of the key factors affecting the competitiveness of electric commercial vehicles: A case study from the USA market , 2013 .

[37]  R. de Lange Elektrisch Vervoer in Amsterdam Onderbouwing van ambitie en doelstelling en adviezen voor een effectieve aanpak , 2009 .