Zonification and Pricing in Carsharing

Abstract

In this article we address the problem of partitioning a carsharing business area into pricing zones. We formalize the problem mathematically and show that the resulting partitioning problem can be formulated as a binary integer programming problem. The partitioning problem is then extended to include pricing decisions, yielding the first joint zonification and pricing problem. The resulting mixed integer (possibly nonlinear) programming problem is solved exactly using an ad-hoc integer Benders decomposition for which we define effective problem-specific improvements. Extensive tests based on a real-world carsharing system demonstrate that the method outperforms a state-of-the-art commercial solver on problems of size comparable to those encountered in real-world instances. Furthermore, by jointly optimizing prices and pricing zones, we observe a profit increase of 7.01% compared to a zip code-based prior partition of the business area, and of 25.61% compared to a scenario where the business area is not partitioned.