Determining optimal road class and road deactivation strategies using dynamic programming

Forest managers are faced with complicated road construction and deactivation decisions. When construction, upgrading, and deactivation strategies must be determined simultaneously over broad spatial and temporal scales, the problem becomes very complex and decision support systems are needed. In this paper, we report the development and application of an optimal road class and deactivation model using dynamic programming. We tested our model on projected road networks on Hardwicke Island, British Columbia. Sensitivity of inputs such as construction costs, upgrade costs, hauling and maintenance costs, deactivation costs, length of time horizon, discount rate, and haul volume were tested within and between two road networks. Comparison of road networks revealed that haul volume concentration, average haul distance, and total road length are the most important variables that affect road class decisions and total network costs. Within our case study, the road network with the lowest average hauling distance resulted in the lowest total cost (CAN$0.24/m³ less), because hauling costs are the largest component (46%) of total transportation costs. The dynamic programming model can be used to assess numerous road construction and maintenance assumptions under various silviculture and harvest systems.