TY - JOUR
T1 - Planning under uncertainty at the forest level: A systems approach
AU - Eriksson Ljusk, Ola
PY - 2006
Y1 - 2006
N2 - Large-scale long-range forest management problems have been successfully analysed for decades using linear programming models. Existing larger systems, such as MELA, FOLPI, FORPLAN, GAYA-LP and Spectrum, are based on a model formulation that is known as model I or the closely related model II. This paper shows how the model I formulation can be extended to incorporate stochastic phenomena. The uncertainty problem is given as a programme with recourse, i.e. the formulation takes account of the fact that the decision maker is able to observe the state of the system over time and subsequently make adaptations. Basic for the formulation is the expression of the stochastic process as a collection of scenarios. After the basic model has been formulated the implications for systems design are indicated. The approach is applied to a small sample forest where the consequences of different objectives and constraints are illustrated. The limitations of the method, among which model size is prominent, are discussed. It is also noted that not all stochastic processes are amenable to analysis with the suggested approach. The procedure requires global, not standwise, processes and there should be no feedback between actions and scenario probabilities.
AB - Large-scale long-range forest management problems have been successfully analysed for decades using linear programming models. Existing larger systems, such as MELA, FOLPI, FORPLAN, GAYA-LP and Spectrum, are based on a model formulation that is known as model I or the closely related model II. This paper shows how the model I formulation can be extended to incorporate stochastic phenomena. The uncertainty problem is given as a programme with recourse, i.e. the formulation takes account of the fact that the decision maker is able to observe the state of the system over time and subsequently make adaptations. Basic for the formulation is the expression of the stochastic process as a collection of scenarios. After the basic model has been formulated the implications for systems design are indicated. The approach is applied to a small sample forest where the consequences of different objectives and constraints are illustrated. The limitations of the method, among which model size is prominent, are discussed. It is also noted that not all stochastic processes are amenable to analysis with the suggested approach. The procedure requires global, not standwise, processes and there should be no feedback between actions and scenario probabilities.
KW - linear programming
KW - long-range forest planning
KW - mixed integer programming
KW - scenario
KW - stochastic
KW - linear programming
KW - long-range forest planning
KW - mixed integer programming
KW - scenario
KW - stochastic
UR - https://res.slu.se/id/publ/9415
UR - http://ejournals.ebsco.com/Article.asp?ContributionID=8651121
U2 - 10.1080/14004080500486849
DO - 10.1080/14004080500486849
M3 - Journal article
SN - 0282-7581
VL - 21
SP - 111
EP - 117
JO - Scandinavian Journal of Forest Research
JF - Scandinavian Journal of Forest Research
ER -