The Chinese Postman Problem and Simulated Annealing applied to urban forest inventory

Routing is the process of defining paths between geographically distinct points, and it has been applied in decision-making processes for services that include displacement, with potential application in the planning of urban forest inventories. Linear Programming is an operations research technique often applied to solve complex problems, such as those related to routing. Thus, the objective of this study was to verify whether the application of a routing model via Integer Linear Programming (ILP) increases the efficiency of an urban forest inventory using real data. First, we compared the empirical division used in the inventory with the application of the ILP method for routing. We also tested an approximate method (Simulated Annealing, SA) to solve the routing problem and reduce the processing time. Finally, we simulated the consequences of applying ILP in different scenarios. The results showed that the ILP improved the inventory efficiency by 6.36%, and the use of SA reduced the processing time by 43,200 times for the most complex scenario, resulting in a solution that was 1.87% of the ILP response value. Our findings show the potential application of ILP in the planning of urban forest inventories, with gains directly proportional to the number of lots in the inventory.