In the forestry industry, the transportation of timber or logs serves as a vital link between forest harvesting areas and demand sites like sawmills, pulp mills, wood panel mills, and various terminals. Given the extensive forest areas and widespread mill locations in many nations, timber transportation constitutes a substantial percentage—often ranging from 20% to 45%—of operational costs within the forest industry. As fossil fuel-based transportation significantly contributes to greenhouse gas emissions, improving transportation efficiencies stands as a key strategy toward reducing these emissions.

The complexities of timber transportation in the forest industry differ markedly from other industries due to numerous factors. It involves traversing long distances and delivering diverse timber assortments in full truckloads across multiple harvesting areas and demand sites. These deliveries utilize a fleet of trucks and trailers or rail transportation, each with varying capacities. Assortments here refer to specific collections of timbers or logs, distinguished by species, dimensions, quality required by demand sites, and their use as pulpwood or saw timber. Typically, large supply volumes leading to multiple visits to each harvesting area or demand site and an unbalance (supply larger than demand) leads to so-called creaming. Timely loading and unloading, facilitated by on-board loading cranes or on-site loaders, align with specific operating hours. Meeting demands might require pickups from multiple supply areas, emphasizing the intricate allocation of supply, demand, assortments, and truck capacities during aggregated planning.

Challenges in forestry logistics

Factors like restricted class roads, private forest roads, and varying weight classes in different countries—such as Sweden’s 64, 74, and 90-ton classes or Norway’s 50, 56, and 60-ton classes—further complicate timber transportation planning, particularly due to the large scale of the problems involved. Also, some countries allow off-road trucks without weight limit on private forest roads.

Timber transportation planning operates under a hierarchical structure encompassing strategic, tactical, and operational planning. Strategic planning, spanning 1-5 years and executed yearly, focuses on determining transportation modes, road construction, terminal locations, and capacities based on aggregated forecasts. This aligns closely with strategic harvesting planning, influencing decisions regarding sustainable forest management and subsequent road network strategies. Tactical planning spans 6-12 months and coordinates supply, demand, assortment allocation, and resource planning, often coinciding with tactical harvesting planning for coordinated transportation operations. Operational planning, conducted daily over weeks, concentrates on determining transportation routes and schedules, necessitating real-time adjustments for day-to-day dispatching.

The operational planning of timber transportation primarily focuses on optimizing routes for a fleet of trucks ferrying timber assortments from harvesting areas to demand sites, constituting what is known as the vehicle routing problem (VRP). The application of Operations Research (OR) to solve complex VRPs in timber transportation gained traction in the 1980s, with ongoing research worldwide in countries like Austria, Canada, Chile, Finland, New Zealand, Australia, Sweden, and the US.

Timber transportation complexities are influenced by various industrial contexts, geographical locations, service structures, fleet ownership, and planning methods. Factors such as long transportation distances, different truck payloads, weather impacts, road ownership, and construction statuses significantly contribute to transportation costs and planning challenges.

Responsibilities for timber transportation from harvest areas to processing mills can vary, with some suppliers managing it while others delegate this responsibility to processing mills. The planning approach, responsibility levels, and decision-making processes vary widely among companies, ranging from decentralized approaches where drivers plan their own trips to centralized approaches led by logistics service providers (LSPs) or independent decision-makers (DMs) managing truck fleets for multiple companies.

Fleet ownership structures in forest transportation also exhibit diversity. Historically, forest companies managed their private crews and truck fleets for harvesting and transportation. However, recent trends involve fewer large private fleets, with some companies utilizing contracted carriers to meet additional transportation requirements. This hybrid strategy aims to reduce costs while retaining essential trucking capacities and in-house knowledge. In certain regions like Central European countries and Canada, fleet ownership is fragmented, with independent owner-operators constituting a significant portion of the truck fleet. This contrasts with areas like the Southern US, where each harvesting contractor manages a small fleet, often using independent owner-operators to supplement specific needs.

Decision support system in forestry

The software developed into decision support systems is typically divided into tactical flow models where the decision variables are continuous variables. Such models are used to determine the best allocation between supply and demand points. It also includes inventory variables to include multiple time periods. More complex models can also be developed where backhauling transports are used. This is an approach to reduce the unloaded distance as most models assume that a loaded trip is combined with an unloaded going back to the supply point. The inclusion of backhaul dramatically increases the model size and special methods based on column generation, where variables are dynamically generated, are needed. Moreover, when transports also include conversion processes, for example conversion of residues to chips, it is also necessary to include processes into the optimization models. The second type is routing models where daily routes are determined for individual trucks. There are many different models here depending on the type of assumptions made, for example full truck load, queuing restrictions, shift time and rest time requirements. Such models are classified into MIP models and are therefore more difficult to solve.

To read more: Reference [1] gives a detailed description of transportation and routing models and methods used in forestry. Reference [2] and [3] describes a standardized system to determine individual routes and an analysis of using different selection of routing, respectively. References [4-6] provides different implementations of either flow or route decision systems in forestry.

[1] J.F. Audy, M. Rönnqvist, S. D’Amours, A-.E. Yiahou, Planning methods and decision support systems in vehicle routing problems for timber transportation: a review, International Journal of Forest Engineering, Vol 34, No. 2, 143-167, 2023

[2] M. Rönnqvist, G. Svenson, P. Flisberg, L.-E. Jönsson, Calibrated Route Finder: Improving the safety, environmental consciousness, and cost effectiveness of truck routing in Sweden, Interfaces, Vol 47 (5), 372-395, 2017.

[3] M. Rönnqvist, P. Flisberg, M. Frisk, D. Bredström, J.-B. Paradis*, A new hybrid method for quick and accurate calculation of forest transportation distances, International Transactions in Operational Research, DOI:10.1111/itor.13409, published online November 2023

[4] P. Flisberg, B. Liden and M. Rönnqvist, A hybrid method based on linear programming and tabu search for routing of logging trucks, Computers & Operations Research, Vol. 36, 1122-1144, 2009.

[5] G. Andersson, P. Flisberg, B. Liden and M. Rönnqvist, RuttOpt – A decision support system for routing of logging trucks, Canadian Journal of Forest Research, Vol. 38, 1784-1796, 2008.

[6] M. Forsberg, M. Frisk, and M. Rönnqvist, FlowOpt – a decision support tool for strategic and tactical transportation planning in forestry, International Journal of Forest Engineering, Vol. 16, No. 2, pp. 101-114, July 2005