Abstract
In this article, we propose a variant of the electric vehicle routing problem considering explicitly the intermediate nodes. Ultimately aiming to provide an optimal routing plan for the shuttle fleet that serves to a university settlement internally, we consider a real road network by explicitly taking into account in the formulation the entire intersections existing and the time-varying passenger demand at shuttle stops, as well as the vehicle dynamics, battery, and recharging features. On purpose, a mathematical program to obtain the joint minimization of a number of objectives in terms of cost, i.e., vehicle operating, battery recharging, and recharging station purchasing, is formulated. Solutions employing an exact method are sought using models of mixed integer program within scenarios involving a number of features including the campus-wide passenger demand, seat capacity of shuttles, battery capacity of shuttles, and recharging station location. Further solutions to our model formulation have been obtained using a benchmark set of instances designed for a large-scale real network. Our findings show that considering a real road network as it is, is significant in exact routing solutions despite the fact that the level of network complexity is an issue. We suggest that a trade-off among the actuality of the network topology and the consequent computational load should be carefully made in order to obtain solutions using exact methods. As is shown, there is room to investigate further in details the dynamics of routing considering especially the effects of changes in flow conditions at intermediate nodes using our formulation.
Original language | English |
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Pages (from-to) | 1223-1235 |
Number of pages | 13 |
Journal | IEEE Transactions on Intelligent Transportation Systems |
Volume | 23 |
Issue number | 2 |
Early online date | 23 Sept 2020 |
DOIs | |
Publication status | Published - Feb 2022 |
Keywords
- Routing
- Roads
- Batteries
- Vehicle routing
- Vehicle dynamics
- Green products
- Electric vehicles
- vehicle routing
- network theory (graphs)
- integer linear programming
- optimization