Routing optimization for ATM cash replenishment

The cash deployment strategy for a network of ATMs should take into account the analysis of inventory policies, logistics costs as well as the routing of replenishment vehicles. The optimal strategy has to focus on the reduction of cash-related expenses while safeguarding that ATMs do not run out of cash. Shorter routes with high time window constraints violations are not always the best solution. The problem, which can be tackled as a kind of rich vehicle routing problem is in the paper solved using parallel genetic algorithm. The proposed model is able to solve cases with simultaneous requirements of several replenishments for some of the customers (ATMs) several times daily as well as a single replenishment in several days for other groups of customers. Dynamic vehicle routing problem (VRP) must rely on up-to-date information. One type of dynamic model may consider new customer orders that arise after the routes had been initially planned. In the light of this information, the vehicles need to be re-routed so as to reduce costs and meet customer service time windows. Keywords— ATM cash replenishment, genetic algorithm, multidepot periodic vehicle routing problem, optimization, time window.