Bi-objective overlapped links vehicle routing problem for risk minimizing valuables transportation

This paper presents a novel variant of the vehicle routing problem (VRP) that considers overlapped links for the transportation of valuables. Maintaining security and minimizing route risks are crucial challenges in the planning and routing of valuable goods whose transport is threatened by risks such as armed robbery and assault. Keeping the transit process secure necessitates, therefore, special planning and routing. A more realistic exam-ination of real-world situations reveals that network routes are not entirely independent and share sections that influence one another. In other words, changing the status of one street section simultaneously affects multiple links. Consequently, a bi-objective overlapped links vehicle routing problem (OLVRP) for valuable goods transportation is developed in this study, where the total cost and risk of routing are minimized. Moreover, a hybrid genetic algorithm is developed to optimize the problem, and its efficiency and effectiveness for small-to -medium and large-scale problems are evaluated. The results demonstrate that the proposed algorithm is superior and highly efficient compared to The non-dominated sorting genetic algorithm II (NSGA-II). Finally, the pro-posed model is used to conduct a real-world case study on cash distribution in Tehran province, Iran, one of the most widely used types of valuable goods transportation.