  Freight truck electrification for last-mile delivery is one of the most
important research topics to reduce the dependency on fossil fuel operations.
Although a battery electric truck still has limitations on daily operations
with lower driving ranges and higher purchasing cost than a conventional truck,
operations with electrified trucks reduce total energy usage and driving noise
on routes. In this paper, we propose a fleet-mix and multi-shift electric
vehicle routing problem for joint implementation of fleet electrification and
off-hour delivery in urban e-commerce delivery systems. Every electrified truck
is assumed to have two shifts for both daytime and nighttime delivery
operations while conventional trucks can operate during daytime only because of
municipal restrictions on nighttime deliveries, which are related to engine
noise. Also, every electrified truck must recharge between shifts at its depot.
A fleet owner decides the best electrification ratio of the fleet and the
proper number of chargers which gives the minimum total cost. The optimization
problem is described as a mixed-integer linear programming model including
common constraints for vehicle routing problem, recharging constraints, and
two-shift operation of electrified trucks. A bi-level VNS-TS heuristic is also
suggested for efficient solution search. The upper-level problem assigns trucks
with engine type and brief route information using variable neighborhood search
heuristic, and the lower-level problem finds the best route of each assigned
truck using a tabu search heuristic. Scenarios with different EV driving ranges
and nighttime operation availabilities are developed and evaluated with the
POLARIS transportation simulation framework, and results are reported.
