Route Optimization of Mobile Medical Unit with Reinforcement Learning

In this paper, we propose a solution for optimizing the routes of Mobile Medical Units (MMUs) in the domain of vehicle routing and scheduling. The generic objective is to optimize the distance traveled by the MMUs as well as optimizing the associated cost. These MMUs are located at a central depot. The idea is to provide improved healthcare to the rural people of India. The solution is obtained in two stages: preparing a mathematical model with the most suitable parameters, and then in the second phase, implementing an algorithm to obtain an optimized solution. The solution is focused on multiple parameters, including the number of vans, number of specialists, total distance, total travel time, and others. The solution is further supported by Reinforcement Learning, explaining the best possible optimized route and total distance traveled.