Integrated Production and Drying-Capacity Planning in Sawmilling: A Multi-Period Mixed Integer Linear Programming Optimization Approach

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Abstract

In lumber production from logs, inventory management is of critical importance due to the natural heterogeneity of raw materials, supply-demand imbalances, and biological degradation risks such as fungal damage. As a multistage and interconnected process involving procurement, sawing, drying, and storage, sawmill operations require coordinated decisions across all stages to maintain efficiency and service reliability. In particular, drying (whether by kiln or natural) often acts as a structural bottleneck, directly influencing lead times, inventory accumulation, and the ability to meet customer demand on time. To address this complexity, this study developed an integrated multiperiod mixed integer linear programming (MILP) model that links raw log procurement, production planning, natural and technical drying allocation, inventory control, and shipment decisions within a unified framework. The model optimizes material flows and capacity utilization while balancing cost efficiency and service performance. A comprehensive sensitivity analysis evaluated the impact of key parameters, including service levels, penalty costs, storage costs, and energy prices. The results indicate that technical (kiln) drying becomes a dominant strategy under high service requirements and elevated shortage penalties, as it enhances system responsiveness and reduces delivery risk. In contrast, natural drying can become competitive under conditions such as lower storage costs or significantly increased energy prices. Overall, the findings provide strategic guidance for sawmill managers and firms considering process upgrades, suggesting that core capacity investments should prioritize technical drying, while natural drying may serve as a complementary flexibility mechanism under appropriate economic conditions.

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