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Introducing cost-plus-loss analysis into a hierarchical forestry planning environment

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  • Karl Duvemo
  • Tomas Lämås
  • Ljusk Eriksson
  • Peder Wikström

Abstract

Cost-plus-loss analysis of data for forestry planning has often been carried out for highly simplified planning situations. In this study, we suggest an advance in the cost-plus-loss methodology that aims to capture the hierarchical structure and iterative nature of planning by the large forest owner. The simulation system that is developed to simulate the planning process of the forest owner includes the tactical and operational levels of a continuous planning process. The system is characterized by annual re-planning of the tactical plan with a planning horizon of ten year and with the option to reassess data for selected stands before operational planning. Operational planning is done with a planning horizon of two years and the first year of the plan is considered to have been executed before moving the planning process one year forward. The annual cycle is repeated 10 times, simulating decisions made over a ten-year time horizon. The optimizing planning models of the system consider wood flow requirements, available harvest resources, seasonal variation of ground conditions and spatiality. The data used are evaluated according to standard procedures in cost-plus-loss analysis. Results from a test case indicate high decision losses when planning at both levels is based on the type of data prevalent in the stand databases of Swedish companies. The losses can be reduced substantially if higher-quality data are introduced before operational planning. In summary, the results indicate that the method makes it possible to analyze where in the planning process one needs better data and their value. Copyright Springer Science+Business Media, LLC 2014

Suggested Citation

  • Karl Duvemo & Tomas Lämås & Ljusk Eriksson & Peder Wikström, 2014. "Introducing cost-plus-loss analysis into a hierarchical forestry planning environment," Annals of Operations Research, Springer, vol. 219(1), pages 415-431, August.
  • Handle: RePEc:spr:annopr:v:219:y:2014:i:1:p:415-431:10.1007/s10479-012-1139-9
    DOI: 10.1007/s10479-012-1139-9
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    References listed on IDEAS

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    1. Andersson, Daniel & Eriksson, Ljusk Ola, 2007. "Effects of temporal aggregation in integrated strategic/tactical and strategic forest planning," Forest Policy and Economics, Elsevier, vol. 9(8), pages 965-981, May.
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    4. John J. McCall, 1982. "The Economics of Information and Uncertainty," NBER Books, National Bureau of Economic Research, Inc, number mcca82-1.
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    6. Eldon A. Gunn, 2007. "Models for Strategic Forest Management," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 317-341, Springer.
    7. Rafael Epstein & Jenny Karlsson & Mikael Rönnqvist & Andres Weintraub, 2007. "Harvest Operational Models in Forestry," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 365-377, Springer.
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    Cited by:

    1. Gang Wang & Angappa Gunasekaran, 2017. "Modeling and analysis of sustainable supply chain dynamics," Annals of Operations Research, Springer, vol. 250(2), pages 521-536, March.

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