Short- and mid-term evaluation of the use of electric vehicles in urban freight transport collaborative networks: a case study

Despite its negative impacts, freight transportation is a primary component of all supply chains. Decision makers have considered diverse strategies, such as Horizontal Collaboration (HC) and the usage of alternative types of vehicles, to reduce overall cost and the related environmental and social impacts. This paper assesses the implementation of an electric fleet of vehicles in urban goods distribution under HC strategy between carriers. A biased randomisation based algorithm is used to solve the problem with a multi-objective function to explore the relationships between both delivery and environmental costs. Real data from the city of Bogota, Colombia are used to validate this approach. Experiments with different costs and demands projections are performed to analyse short- and medium-term impacts related to the usage of electric vehicles in collaborative networks. Results show that the optimal selection of vehicle types depends considerably on the time horizon evaluation and demand variation.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT) and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Special Patrimonial Fund from Universidad de La Sabana (Colombia) and the doctoral grant from the UOC-Open University of Catalonia (Spain)

A Vehicle Routing Problem with Payload-Range Dependency by Fuel Consumption

In this research, a new variant of vehicle routing problem is introduced. Fuel consumption constitutes a significant component of transportation costs especially when large volumes of goods are transported using means of transportation such as aircrafts. Hence, the objective of this research is to perform efficient routing of a heterogeneous fleet of vehicles such that fuel consumption costs are minimized. Reduced fuel consumption also reduces greenhouse gases emission and creates a positive impact on the environment. Another unique characteristic studied is the dependence between load carried by a vehicle and the maximum distance it can travel without stopping. Weight of fuel is considered along with the load carried for vehicle capacity constraints. Split delivery and time window constraints are also considered. A mathematical model for the new problem has been developed. It has been implemented to solve a real-world case study for express delivery of goods. An initial solution greedy algorithm and a tabu search heuristic algorithm have also been developed in order to solve large scale instances of the problem. Comparison with optimal solution suggests that a good solution can be obtained using the heuristic algorithm in relatively short time

A review of recent advances in the operations research literature on the green routing problem and its variants

Since early 2010s, the Green Routing Problem (GRP) has dominated the literature of logistics and transportation. The problem itself consists of finding a set of vehicle routes for a set of customers while minimizing the detrimental effects of transportation activities. These negative externalities have been intensively tackled in the last decade. Operations research studies have particularly focused on minimizing the energy consumption and emissions. As a result, the rich literature on GRPs has already reached its peak, and several early literature reviews have been conducted on various aspects of related vehicle routing and scheduling problem variants. The major contribution of this paper is that it represents a comprehensive review of the current reviews on GRP studies. In addition to that, it is an up-to-date review based on a new chronological taxonomy of the literature. The detailed analysis provides a useful framework for understanding the research gaps for the future studies and the potential impacts for the academic community