A mixed-integer optimization approach to assess timber hauling cost increases under bridge restrictions

This study uses a mixed-integer linear programming (MILP) optimization model to evaluate bridge weight restrictions on pine sawlog transportation costs in Mississippi, USA. Results reveal that restricted bridges increased transportation costs by $4.09 million ($ USD), a 4.07% rise, or $0.37 per tonne, requiring an additional 12,410 truckloads to meet fiber sourcing goals. The impacts were most severe for sawmills located in regions with dense clusters of restricted bridges, particularly along the Interstate Highway 20 corridor in Central Mississippi, where high timber demand amplifies cost inefficiencies. Routes, paired specific harvest sites with sawmill facilities, experienced disproportionately high-cost increases, with per-tonne costs rising by up to $3.92 ($ USD). Spatial disparities highlight those regions with limited alternative routes and high mill demand are particularly vulnerable to bridge-related disruptions. Addressing these infrastructure challenges through targeted bridge maintenance and investment is essential to support the economic viability of the forest sector and enhance supply chain resilience across the Southeastern United States.