Finding the relevance of staff-based vehicle relocations in one-way carsharing systems through the use of a simulation-based optimization tool

Abstract

This paper proposes a real-time decision support tool based on the rolling-horizon principle that manages staff activities (relocations and maintenance) of a one-way carsharing system and considers carpooling the staff in the relocated carsharing vehicles for extra cost reduction. The decision support tool is composed of three elements: a forecasting model, an assignment model and a filter. Two assignment models are proposed and tested: rule-based and optimization. The rule-based model uses simple rules to respond to system status changes, and the optimization model is a mixed integer programing (MIP) model prepared to work in real-time. A simulator was designed to test the decision support tool and an application is done to the city of Lisbon, Portugal, showing that the benefits of staff relocations can be rather low. It was verified that the number of relocations that can physically be performed by each staff member in the case study provide only a small improvement in the revenues, which is unlikely to overcome the costs associated with hiring and staff activity.