Risk-based cooperative vehicle routing problem for cash-in-transit scenarios: A hybrid optimization approach

The banking sector, a pivotal player in the economic system, faces intricate challenges in managing the cash deployment strategy for Automated Teller Machine (ATM) networks. This strategy necessitates a comprehensive consideration of inventory policies, logistics costs, and replenishment vehicle routing. Similar to other organizations, banks are dedicated to offering optimal services to customers, with cash availability at each branch serving as a critical metric. This is typically facilitated by Cash-in-Transit (CIT) firms, which, in the process of transferring money between branches, encounter potential risks such as robberies with severe consequences. To mitigate these risks and associated costs, CIT firms have turned to solving Vehicle Routing Problems (VRP). This study delves into optimizing CIT's vehicle routing through a proposed cooperative mathematical VRP model, incorporating two objective functions aimed at minimizing both risk and cost. The results section commences with an analysis of a real bank's transportation system, revealing a trade-off between cost and risk. This underscores the significance of integrating risk considerations into money transfer routing models. The cooperative approach model is subsequently employed to assess effectiveness in optimizing vehicle routing for CIT firms. Robust optimization yields numerical results indicating that increased collaboration among banks results in synergies in terms of risk and cost reduction. The highest synergy is observed when cooperating with the maximum number of banks (four), leading to the most significant savings in both risk and cost aspects.(c) 2024 by the authors; licensee Growing Science, Canada