A Mathematical Formulation for the Location of Logging Camps

Logging activities within the forestry sector commonly take several seasons for each region. Throughout each season, the workers directly involved within the logging activities are hosted at an accommodation close to the current logging location. However, the next cities or villages are usually far away. A common solution to this problem is the construction of logging camps that contain the complete infrastructure to host the workers. Such logging camps are typically close to the logging regions, resulting in reasonable transportation times and costs. The bigger a camp, the lower the daily hosting costs per person. Hence, a small number of big camps results in lower accommodation costs than a large number of small camps. However, the fewer camps are available, the higher the transportation costs tend to be, because their geographic distribution is less flexible. The problem studied in this paper consists in finding the optimal number, location and size of logging camps. Due to the complexity of the problem, a manual planning approach is not applicable. This work investigates the relevance and advantages of constructing additional camps for the accommodation of workers, expanding the capacities of existing camps and relocating entire camps from one region to another. A mathematical model, representing the cost structure on a very detailed level is presented. Results are given for a realistic five year harvest planning provided by FPInnovations and based on data from a Canadian logging company. CONTEXT AND MOTIVATION Log harvest planning in the forestry sector changed throughout the last decades. Both silviculture and harvesting became more sophisticated and include very complex and important decisions in order to get the most from the available regions and harvest cycles. Based on a complex variety of such considerations, a long-term planning is designed to determine the volume and regions for wood logging. Such decisions are commonly divided into smaller time periods.