Transportation is a main component of supply chain competitiveness since it plays a major role in the inbound, inter-facility, and outbound logistics. In this context, assigning and scheduling vehicle routing is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic nature of this problem. In this paper, a vehicle routing problem and stochastic travel time due to potential traffic congestion is considered. The approach developed introduces mainly the traffic congestion component that is combined with an Ants Colony Optimization heuristic. Standard test problems are used for illustrative purposes as well as for a discussion around the feasibility of proposed solutions if travel times were not constant. In future, more extensions will be made to this basic framework to solve the stochastic VRP (Vehicle Routing Problem). First, the daemon actions that explicitly take into account congestion seem to contribute substantially to the solution quality. Consequently, new dynamic improvement heuristics should be developed. For instance, once the total route is known, there is the possibility that it can be improved by adding the depot in each subtour. This will result in a shorter route in terms of travel time but the route will be covering more distance with an additional truck. The developed approach will also be applied to the VRP with the addition of time windows.
A vehicle routing problem with stochastic travel times
Ein Fahrzeugstreckenführungsproblem mit stochastischen Fahrzeiten
2003
10 Seiten, 1 Bild, 2 Tabellen, 24 Quellen
Aufsatz (Konferenz)
Englisch
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