4 research outputs found
Pricing routines for vehicle routing with time windows on road networks
Several very effective exact algorithms have been developed for vehicle routing problems with time windows. Unfortunately, most of these algorithms cannot be applied to instances that are defined on road networks, because they implicitly assume that the cheapest path between two customers is equal to the quickest path. Garaix and coauthors proposed to tackle this issue by first storing alternative paths in an auxiliary multi-graph, and then using that multi-graph within a branch-and-price algorithm. We show that, if one works with the original road network rather than the multi-graph, then one can solve the pricing subproblem more quickly, in both theory and practice
Pricing routines for vehicle routing with time windows on road networks
Several very effective exact algorithms have been developed for vehicle routing problems with time windows. Unfortunately, most of these algorithms cannot be applied to instances that are defined on road networks, because they implicitly assume that the cheapest path between two customers is equal to the quickest path. Garaix and coauthors proposed to tackle this issue by first storing alternative paths in an auxiliary multi-graph, and then using that multi-graph within a branch-and-price algorithm. We show that, if one works with the original road network rather than the multi-graph, then one can solve the pricing subproblem more quickly, in both theory and practice
The Bi-objective Long-haul Transportation Problem on a Road Network
In this paper we study a long-haul truck scheduling problem where a path has
to be determined for a vehicle traveling from a specified origin to a specified
destination. We consider refueling decisions along the path, while accounting
for heterogeneous fuel prices in a road network. Furthermore, the path has to
comply with Hours of Service (HoS) regulations. Therefore, a path is defined by
the actual road trajectory traveled by the vehicle, as well as the locations
where the vehicle stops due to refueling, compliance with HoS regulations, or a
combination of the two. This setting is cast in a bi-objective optimization
problem, considering the minimization of fuel cost and the minimization of path
duration. An algorithm is proposed to solve the problem on a road network. The
algorithm builds a set of non-dominated paths with respect to the two
objectives. Given the enormous theoretical size of the road network, the
algorithm follows an interactive path construction mechanism. Specifically, the
algorithm dynamically interacts with a geographic information system to
identify the relevant potential paths and stop locations. Computational tests
are made on real-sized instances where the distance covered ranges from 500 to
1500 km. The algorithm is compared with solutions obtained from a policy
mimicking the current practice of a logistics company. The results show that
the non-dominated solutions produced by the algorithm significantly dominate
the ones generated by the current practice, in terms of fuel costs, while
achieving similar path durations. The average number of non-dominated paths is
2.7, which allows decision makers to ultimately visually inspect the proposed
alternatives