DescriptionElectric mobility is characterized by a clean and noiseless drive alongside a limited driving range. It serves the purpose of urban logistics almost perfectly catering to short distances in city centers and to the onus to maintain air quality and reduce noise pollution in densely populated areas. A general urban service logistics problem with a mixed fleet including electric vehicles, compatibility specification between customers’ requests and drivers’ skills, and time windows is considered. In our formulation, we propose an upgrade to the energy consumption model to account for auxiliary loads during the drive. We develop a novel adaptive large neighborhood search algorithm to solve the operational problem on each day.
To understand the influence of factors such as temperature, time window tightness, spread of customers, etc. on the total cost of fleet ownership, we perform a simulation analysis on two real case studies from Copenhagen. In the first case study, we look into electrician routing for a construction firm, MT Hojgaard, using a mixed fleet of vehicles (both electric and non-electric), while in the other, we work with Region Hovedstaten to efficiently plan the pick-up logistics of temperature-controlled, time-sensitive transport of blood samples from clinics to a testing laboratory using a mixed fleet of electric vehicles.
This work is aimed towards developing decision-making tools that enable a smooth transition to electric mobility.
|Period||23 Jun 2019 → 26 Jun 2019|
|Event title||30th European Conference On Operational Research<br/>|
|Degree of Recognition||International|