Soluzioni esatte e approcci euristici per il bilanciamento statico ed equo di flotte di veicoli elettrici in sharing

Urban transport systems, including bike and scooter sharing, face significant challenges in vehicle management, especially with e-vehicles requiring regular recharging and maintenance. This thesis focuses on optimizing the rebalancing of e-vehicles in sharing systems. Initially, a Mixed Integer Linear Programming (MILP) model is implemented and validated to address the static relocation vehicle problem, integrating a Gini-based equity index to balance various objective function components. Key contributions include the implementation of state-of-the-art constraint generation procedures to efficiently find exact optimal solutions or lower bounds. Additionally, a heuristic algorithm is developed to achieve near-optimal solutions, which are then integrated into the exact procedures for faster resolution.