Solution approaches to reduce problems with unbalanced supply and demand in transportation and harvest planning

ABSTRACT

This study addresses forestry planning challenges arising from supply-demand imbalances. In forest planning, supply often exceeds demand because supplies are known in advance, while demands are known more short term when ordered. This leads to so-called “creaming,” where forest planners select nearby areas first. With static supply and incremental demand information, average transportation distance increases over the planning horizon. To mitigate this, we propose an approach to artificially balance supply and demand. This can be achieved by including additional time periods with additional demand making up the factual difference. We evaluate three planning approaches to model the extended demand, varying the number of time periods and extension duration. Through simulations, we compare these approaches to traditional methods and theoretical solutions. Our proposed approach aims to better keep the average distance balanced throughout the overall planning periods. It ensures that average transportation distances are not excessively favorable in the initial periods, nor unreasonably high in the later periods, resulting in a favorable equilibrium in the average transportation distance over time. It makes sure that we do not need the additional truck capacity at certain times. We assess our proposed approaches using a case study from a Swedish forestry company, demonstrating their superiority over current practices.

KEYWORDS:

• Transportation
• forest operations
• dynamic forecasting
• anticipative planning

Acknowledgements

The authors would like to thank the FORAC Research Consortium at Université Laval and its industrial partners for funding this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).