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2334. The Robust Bike Sharing Rebalancing Problem: Formulations and a Branch-and-Cut Algorithm

Invited abstract in session MA-35: Robust and Stochastic Routing Problems, stream Stochastic, Robust and Distributionally Robust Optimization.

Monday, 8:30-10:00
Room: 44 (building: 303A)

Authors (first author is the speaker)

1. Bruno Bruck
Universidade Federal da Paraíba
2. Walton Pereira Coutinho
Industrial Engineering - CAA, Federal University of Pernambuco
3. Pedro Munari
Production Engineering Department, Federal University of Sao Carlos

Abstract

Bike sharing systems (BSSs) are an important component of sustainable urban transportation, providing flexible and eco-friendly alternatives for city logistics. However, these systems often face challenges with unbalanced bike distribution among stations, requiring rebalancing operations to ensure efficient operations. Adding to this complexity is the uncertain demand at stations, which can further complicate rebalancing efforts even during off-peak hours. This work introduces the Robust Bike Sharing Rebalancing Problem (RBRP), which employs robust optimization to improve rebalancing operations in BSSs. Despite the significant impact of uncertainty on system performance, few studies have addressed this aspect in the literature. We propose two new formulations and a tailored branch-and-cut algorithm for the RBRP. The first formulation is compact, leveraging the linearization of recursive equations, while the second relies on robust rounded capacity inequalities and feasibility cuts. Computational results based on benchmark instances demonstrate the effectiveness of our approaches, highlighting the benefits of robust solutions in supporting decision-making for BSSs.

Keywords

Status: accepted

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