Related papers: Electric Vehicle Routing Problem with Time Windows…
Electric vehicle (EV) charging patterns are highly uncertain in both location, time, and duration particularly in association with the predicted high demand for electric mobility in the future. An EV can be charged at home, at charging…
Electric trucks are increasingly deployed to reduce the trucking sector's carbon footprint, but their limited range and charging needs create operational challenges on mid- to long-haul routes. Truck platooning can mitigate range anxiety…
Electric vehicles (EVs) are being rapidly adopted due to their economic and societal benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend. However, the long charging time and high recharging frequency of EVs pose…
The multi-vehicle covering tour problem with time windows (MCTPTW) aims to construct a set of maximal coverage routes for a fleet of vehicles that serve (observe) a secondary set of sites given a fixed time schedule, coverage requirements,…
We study the carbon footprint optimization (CFO) of a heavy-duty e-truck traveling from an origin to a destination across a national highway network subject to a hard deadline, by optimizing path planning, speed planning, and intermediary…
We study Electric Vehicle (EV) charging from a scheduling perspective, aiming to minimize delays while respecting the grid constraints. A network of parking lots is considered, each with a given number of charging stations for electric…
The ecological transition and the reduction of pollution are reasons for the use of green logistic and non-polluting vehicles. In this sense, electric vehicles are an alternative and in recent years many technological advances have been…
Range anxiety has been the main challenge for the mass-adoption of electric vehicles (EVs). The emerging mobile electric-vehicle-to-electric-vehicle (mE2) charging technology, which allows an EV with the extra battery to charge the other EV…
Despite the rapid proliferation of Internet of Things applications driving widespread wireless sensor network (WSN) deployment, traditional WSNs remain fundamentally constrained by persistent energy limitations that severely restrict…
The use of electric vehicles (EV) in the last mile is appealing from both sustainability and operational cost perspectives. In addition to the inherent cost efficiency of EVs, selling energy back to the grid during peak grid demand, is a…
Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and…
The main objective of this paper is to design electric vehicle (EV) charging policies which minimize the impact of charging on the electricity distribution network (DN). More precisely, the considered cost function results from a linear…
Platooning of vehicles is a promising approach for reducing fuel consumption, increasing vehicle safety, and using road space more efficiently. We consider the important but difficult problem of assigning optimal routes and departure…
Temporal dependencies between customer visits, such as synchronization constraints, pose a fundamental challenge in vehicle routing. These dependencies, which arise in applications such as home healthcare routing, aircraft scheduling, and…
The rapid rise of electric vehicles (EVs) places unprecedented stress on both urban mobility systems and low-voltage power grids. Designing battery swapping and charging networks that are cost-efficient, grid-compatible, and sustainable is…
Due to the ongoing electrification of transport in combination with limited power grid capacities, efficient ways to schedule the charging of electric vehicles (EVs) are needed for the operation of, for example, large parking lots. Common…
Public charging infrastructure plays a crucial role in the context of electrifying the private mobility sector in particular for urban regions. Against this background, we develop a new mathematical model for the optimal placement of public…
In this work, we consider learning-based applications in routing to solve a Vehicle Routing variant characterized by stochasticity and multiple objectives. Such problems are representative of practical settings where decision-makers have to…
Most navigation systems use data from satellites to provide drivers with the shortest-distance, shortest-time or highway-preferred paths. However, when the routing decisions are made for advanced vehicles, there are other factors affecting…
The "avoid - shift - improve" framework and the European Clean Vehicles Directive set the path for improving the efficiency and ultimately decarbonizing the transport sector. While electric buses have already been adopted in several cities,…