Abstract
One possibility of coordinating service requests that arise for vehicles of a carsharing fleet is to optimize routes of shuttles that drop off and pick up service agents. This scenario is modeled as a variant of Vehicle Routing Problem (VRP), including aspects of the VRP with Time Windows, the Team Orienteering Problem and the Pick-Up and Delivery Problem. A metaheuristic, an Adaptive Large Neighborhood Search is adapted, tested by applying real-world data and evaluated regarding performance and run time. The results show that, despite high run times to improve the initial solution several times, a feasible solution is obtained quickly. Some very practicable routes are obtained when including the minimization of the latest arrival time in the hierarchical objective function. Then, all shuttles are occupied evenly and results reach a high number of served requests. The algorithm can support fleet managers to handle a complex problem within their daily business.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
