Annals of Operations Research

, Volume 190, Issue 1, pp 93–115 | Cite as

Supply network planning in the forest supply chain with bucking decisions anticipation

  • Satyaveer S. Chauhan
  • J.-M. FrayretEmail author
  • Luc LeBel


We consider a two-echelon timber supply chain in which the first echelon consists of several stands to be harvested and the second echelon consists of mills to be supplied with logs of different length. This problem aims at minimizing harvesting and transportation costs for one production period, while satisfying demand expressed as a mix of volumes of specific log types. Harvesting cost, which includes felling, bucking and hauling to roadside, depends upon the number of log type to be produced and sorted. Each stand to be harvested is modeled individually with a limited number of trees of various classes of diameter and total length, which affects the productivity factors of the bucking patterns to be used. To take these characteristics into account, we propose heuristics based on columns generation to solve the supply network problem at the forest level with an anticipation of bucking operations at the stand level.


Supply network planning Bucking Integer programming Heuristic Forest supply chain Columns generation 


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  1. Arce, J. E., Carnieri, C., Sanquetta, C. R., & Filho, A. F. (2002). A forest-level Bucking optimization system that considers customer’s demand and transportation costs. Forest Science, 48(3), 492–503. Google Scholar
  2. Beaudoin, D., LeBel, L., & Frayret, J. M. (2007). Tactical supply chain planning in the forest products industry through optimisation and scenario-based analysis. Canadian Journal of Forest Research, 37(1), 128–140. CrossRefGoogle Scholar
  3. Beaudoin, D., Frayret, J.-M., & LeBel, L. (2008). Hierarchical forest management with anticipation: an application to tactical-operational planning integration. Canadian Journal of Forest Research, 38(8), 2198–2211. CrossRefGoogle Scholar
  4. Burger, D. H., & Jamnick, M. S. (1995). Using linear programming to make wood procurement decisions. Forestry Chronicle, 71(1), 89–96. Google Scholar
  5. Brunberg, T., & Arlinger, J. (2001). Vad kostar det att sortera virket i skogen? (What does it cost to sort timber at the stump?). Resultat, Skogforsk 3. Google Scholar
  6. Carlsson, D., & Rönnqvist, M. (2005). Supply chain management in forestry—case studies at Södra Cell AB. European Journal of Operational Research, 163(3), 589–616. CrossRefGoogle Scholar
  7. Chauhan, S. S., Frayret, J.-M., & LeBel, L. G. (2009). Multi-commodity supply network planning in the forest supply chain. European Journal of Operational Research 196(2), 688–696. CrossRefGoogle Scholar
  8. Eng, G., & Daellenbach, H. G. (1985). Forest outturn optimization by Dantzig-Wolfe decomposition and dynamic programming column generation. Operations Research, 33(2), 459–464. CrossRefGoogle Scholar
  9. Epstein, R., Nieto, E., Weintraub, A., Chevalier, P., & Gabarro, J. (1999). A system for the design of short term harvesting strategy. European Journal of Operational Research, 119(2), 427–439. CrossRefGoogle Scholar
  10. Faaland, B., & Briggs, D. (1984). Log bucking and lumber manufacturing using dynamic programming. Management Science, 30(2), 245–257. CrossRefGoogle Scholar
  11. Flisberg, P., Forsberg, M., & Ronnqvist, M. (2007). Optimization based planning tools for routing of forwarders at harvest area. Canadian Journal of Forest Research, 37(11), 2153–2163. CrossRefGoogle Scholar
  12. Forintek Canada, F. (2005). Efficacité du tronçonnage a la scierie et en foret a l’aide de multifonctionnelles. Technote Forintek June. Google Scholar
  13. Geerts, J. M. P., & Twaddle, A. A. (1984). A method to assess log value loss caused by cross-cutting practice on the skidsite. New Zealand Journal of Forestry, 29(2), 173–184. Google Scholar
  14. Gingras, J.-F., & Favreau, J. (2002). Incidence du triage sur la productivité des systémes par bois tronçonnés. Avantage, Feric 3. Google Scholar
  15. Gunnarsson, H., Rönnqvist, M., & Lundgren, J. (2004). Supply chain modeling of forest fuel. European Journal of Operational Research, 158(1), 103–123. CrossRefGoogle Scholar
  16. Karlsson, J., Rönnqvist, M., & Bergström, J. (2003). Short-term harvest planning including scheduling of harvest crews. International Transactions in Operational Research, 10(5), 413–431. CrossRefGoogle Scholar
  17. Karlsson, J., Rönnqvist, M., & Bergström, J. (2004). An optimization model for annual harvest planning. Canadian Journal of Forest Research, 34, 1747–1754. CrossRefGoogle Scholar
  18. Kivinen, V. P. (2004). A genetic algorithm approach to tree bucking optimization. Forest Science, 50(5), 696–710. Google Scholar
  19. Kivinen, V. P. (2006). A forest-level genetic algorithm based control system for generating stand-specific log demand distributions. Canadian Journal of Forest Research, 36(7), 1705–1722. CrossRefGoogle Scholar
  20. Kivinen, V. P., & Uusitalo, J. (2002). Applying fuzzy logic to tree bucking control. Forest Science, 48(4), 673–684. Google Scholar
  21. Laroze, A. (1999). A Linear Programming, Tabu Search method for solving forest-level bucking optimization problems. Forest Science, 45(1), 108–116. Google Scholar
  22. Laroze, A. J., & Greber, B. J. (1997). Using Tabu Search to generate stand-level, rule-based bucking patterns. Forest Science, 43(2), 157–169. Google Scholar
  23. Maness, T., & Adams, D. (1991). The Combined Optimization of Log Bucking and Sawing Strategies. Wood and Fiber Science, 23(2), 296–314. Google Scholar
  24. Marshall, H. D., Murphy, G., & Boston, K. (2006). Three mathematical models for bucking-to-order. Silva Fennica, 40(1), 127–142. Google Scholar
  25. Martell, L. M., Gunn, E. A. et al. (1998). Forest management challenges for operational researchers. European Journal of Operational Research, 104(1), 1–17. CrossRefGoogle Scholar
  26. Mendoza, G., & Bare, B. (1986). A Two-stage decision model for bucking and allocation. Forest Products Journal, 36(10), 70–74. Google Scholar
  27. Murphy, G., Marshall, H., & Bolding, M. C. (2004). Adaptive control of bucking on harvesters to meet order book constraints. Forest Products Journal, 54(12), 114–121. Google Scholar
  28. Pnevmaticos, S. M., & Mann, S. H. (1972). Dynamic programming in tree bucking. Forest Products Journal, 22(2), 26–30. Google Scholar
  29. Rönnqvist, M. (2003). Optimization in forestry. Mathematical Programming, Series B, 97(1–2), 267–284. Google Scholar
  30. Sessions, J., Boston, K., Hill, R., & Stewart, R. (2005). Log sorting location decisions under uncertainty. Forest Products Journal, 55(12), 53–57. Google Scholar
  31. Sessions, J., Olsen, E., & Garland, J. (1989). Tree bucking for optimal stand value with log allocation constraints. Forest Science, 35(1), 271–276. Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Satyaveer S. Chauhan
    • 1
  • J.-M. Frayret
    • 2
    • 3
    Email author
  • Luc LeBel
    • 3
    • 4
  1. 1.Department of Decision Sciences and Management Information Systems, John Molson School of BusinessUniversity of ConcordiaMontréalCanada
  2. 2.Département de Mathématique et de Génie IndustrielÉcole Polytechnique de MontréalMontréalCanada
  3. 3.Consortium de Recherche FOR@CUniversité LavalQuébecCanada
  4. 4.Faculté de Foresterie et de GéomatiqueUniversité LavalQuébecCanada

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