This paper presents a novel extension of vehicle routing problem considering alternative green-fuel powered vehicles in the presence of congestion, with the aim of minimizing CO2 emissions. The travel time and fuel consumption on each arc are not only dependent on the distance traveled, but also they are dependent on the time of the day at which that arc is traversed, as well. Moreover, since refueling infrastructures are limited, refueling decisions should be integrated into the route planning. First, this problem is formulated as a mixed integer linear programming model. Then, a hybrid heuristic algorithm, consisting of two phases, is proposed to solve large instances. The first phase decomposes the problem into clustering and routing stages; and the second phase is a simulated annealing framework trying to improve the solution obtained by the first phase. Computational experiments over randomly generated instances confirm that our algorithm is able to find near optimal solutions to large size instances in at most 2000s.
https://doi.org/10.1007/s12667-018-0283-yCite as:
@article{Hooshmand_2018,
doi = {10.1007/s12667-018-0283-y},
url = {https://doi.org/10.1007%2Fs12667-018-0283-y},
year = 2018,
month = {mar},
publisher = {Springer Science and Business Media {LLC}},
volume = {10},
number = {3},
pages = {721--756},
author = {F. Hooshmand and S. A. MirHassani},
title = {Time dependent green {VRP} with alternative fuel powered vehicles},
journal = {Energy Systems}
}