2866. Routing a mixed fleet for on-site services considering EV charging and time windows
Invited abstract in session TD-56: Routing with Time Windows, stream Vehicle Routing and Logistics.
Tuesday, 14:30-16:00Room: Liberty 1.11
Authors (first author is the speaker)
| 1. | Jiyin Liu
|
| Loughborough Business School, Loughborough University | |
| 2. | Vidura Sooriyaarachchi
|
| School of Business And Economics, Loughborough University | |
| 3. | Rupal Mandania
|
| Loughborough University |
Abstract
This study addresses a problem of scheduling on-site service tasks and routing the vehicles that technicians drive to the sites to perform the tasks. With increasing number of Electric Vehicles (EVs) in the fleet, EV charging needs to be considered in the planning in addition to customer time windows and other constraints. The objective is to minimise travel cost as well as the extra cost for charging EVs during the day. The problem is formulated as a mixed-integer linear programming model. Considering the complexity of the problem, a variable neighbourhood search-based heuristic is applied to solve the problem of practical size. The heuristic searches for the best allocation of tasks and the best sequences of tasks in vehicle routes. An efficient dynamic programming algorithm is developed to check feasibility and optimising the charging for a given route. This algorithm is imbedded in the heuristic to calculate the objective value for each for each solution searched. Results of computational experiments will be presented to demonstrate the effectiveness of the method and the impact of problem parameters on the solution.
Keywords
- Vehicle Routing
- Metaheuristics
- Mathematical Programming
Status: accepted
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