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Articles containing the keyword 'decision analysis'

Category : Article

article id 5484, category Article
Jyrki Kangas, Timo Pukkala. (1992). A decision theoretic approach applied to goal programming of forest management. Silva Fennica vol. 26 no. 3 article id 5484. https://doi.org/10.14214/sf.a15645
Keywords: forest management; models; forest planning; decision analysis; goal programming; optimization methods
Abstract | View details | Full text in PDF | Author Info

An alternative approach to formulating a forestry goal programming problem is presented. First, single objective optima levels are solved. The Analytical Hierarchy Process is applied in the estimation of a priori weights of deviations from the goal target levels. The ratios of the weights can be interpreted as relative importance of the goals, respectively. The sum of the weighted deviations from all single optima levels associated with the management goals is minimized. Instead of absolute deviations, relative ones are used. A case study problem of forest management planning with several objectives, measured in different units, is analysed.

The PDF includes an abstract in Finnish.

  • Kangas, E-mail: jk@mm.unknown (email)
  • Pukkala, E-mail: tp@mm.unknown

Category : Article

article id 7513, category Article
Jyrki Kangas, Teppo Loikkanen, Timo Pukkala, Jouni Pykäläinen. (1996). A participatory approach to tactical forest planning. Acta Forestalia Fennica no. 251 article id 7513. https://doi.org/10.14214/aff.7513
Keywords: forest planning; public participation; optimization; heuristics; conflict management; decision analysis; participative planning
Abstract | View details | Full text in PDF | Author Info

The paper examines the needs, premises and criteria for effective public participation in tactical forest planning. A method for participatory forest planning utilizing the techniques of preference analysis, professional expertise and heuristic optimization is introduced. The techniques do not cover the whole process of participatory planning, but are applied as a tool constituting the numerical core for decision support. The complexity of multi-resource management is addressed by hierarchical decision analysis which assesses the public values, preferences and decision criteria toward the planning situation. An optimal management plan is sought using heuristic optimization. The plan can further be improved through mutual negotiations, if necessary. The use of the approach is demonstrated with an illustrative example. Its merits and challenges for participatory forest planning and decision making are discussed and a model for applying it in general forest planning context is depicted. By using the approach, valuable information can be obtained about public preferences and the effects of taking them into consideration on the choice of the combination of standwise treatment proposals for a forest area. Participatory forest planning calculations, carried out by the approach presented in the paper, can be utilized in conflict management and in developing compromises between competing interests.

  • Kangas, E-mail: jk@mm.unknown (email)
  • Loikkanen, E-mail: tl@mm.unknown
  • Pukkala, E-mail: tp@mm.unknown
  • Pykäläinen, E-mail: jp@mm.unknown

Category : Research article

article id 937, category Research article
Rene Zamora-Cristales, Kevin Boston, John Sessions, Glen Murphy. (2013). Stochastic simulation and optimization of mobile chipping economics in processing and transport of forest biomass from residues. Silva Fennica vol. 47 no. 5 article id 937. https://doi.org/10.14214/sf.937
Keywords: forest planning; simulation; optimization; economics; decision analysis; forest biomass; renewable energy
Highlights: A stochastic simulation model is proposed to analyze forest biomass operations; The cost of chipper and truck waiting times was estimated in forest biomass recovery operations; The economic effect of truck-machine interactions under uncertainty was analyzed; Road characteristics and processing location have an economic impact in truck and chipper waiting times
Abstract | Full text in HTML | Full text in PDF | Author Info
We analyzed the economics of mobile chipping and transport of biomass from forest residues for energy purposes under uncertainty. A discrete-event simulation model was developed and utilized to quantify the impacts of controllable and environmental variables on productivity in order to determine the most cost effective transportation options under steep terrain conditions. Truck-chipper interactions were analyzed to show their effect on truck and chipper standing time. A costing model was developed to account for operating and standing time cost (for the chipper and trucks). The model used information from time studies of each activity in the productive cycle and spatial-temporal information obtained from geographic information system (GIS) devices, and tracking analysis of machine and truck movements. The model was validated in field operations, and proved to be accurate in providing the expected productivity. A cost distribution was elaborated to support operational decisions of forest managers, landowners and risk-averse contractors. Different scenarios were developed to illustrate the economic effects due to changes in road characteristics such as in-highway transport distance, in-forest internal road distance and pile to trailer chipper traveling distances.
  • Zamora-Cristales, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: rene.zamora@oregonstate.edu (email)
  • Boston, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: kevin.boston@oregonstate.edu
  • Sessions, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: john.sessions@oregonstate.edu
  • Murphy, Waiariki Institute of Technology, Rotorua, New Zealand E-mail: glen.murphy@waiariki.ac.nz
article id 651, category Research article
Annika S. Kangas, Jyrki Kangas. (1999). Optimization bias in forest management planning solutions due to errors in forest variables. Silva Fennica vol. 33 no. 4 article id 651. https://doi.org/10.14214/sf.651
Keywords: forest planning; uncertainty; prediction; decision analysis
Abstract | View details | Full text in PDF | Author Info
The yield of various forest variables is predicted by means of a simulation system to provide information for forest management planning. These predictions contain many kinds of uncertainty, for example, prediction and measurement errors. Inevitably, this has an effect on forest management planning. It is well known that uncertainty in the forest yields causes optimistic bias in the observed values of the objective function. This bias increases with the error variances. The amount of bias, however, also depends on the error structure and the relations between the objective variables. In this paper, the effect of uncertainty in forest yields on optimization is studied by simulation. The effect of two different sources of error, the correlation structure of these errors and relations among the objective variables are considered, as well as the effect of two different optimization approaches. The relations between the objective variables and the error structure had a notable effect on the optimization results.
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: annika.kangas@metla.fi (email)
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jk@nn.fi
article id 677, category Research article
Pekka Leskinen, Jyrki Kangas. (1998). Analysing uncertainties of interval judgment data in multiple-criteria evaluation of forest plans. Silva Fennica vol. 32 no. 4 article id 677. https://doi.org/10.14214/sf.677
Keywords: forest planning; uncertainty; decision analysis; expert judgment; pairwise comparisons
Abstract | View details | Full text in PDF | Author Info
The use of interval judgments instead of accurate pairwise comparisons has been proposed as a solution to facilitate the analysis of uncertainties in the widely applied pairwise comparisons technique. A method is presented for deriving probability distributions for the pairwise comparisons and for utilizing the distributions in the analysis of uncertainties in the evaluation process. The first step is that the expert or the decision-maker is queried as to the best guess of the priority ratio of the attributes compared. This is followed by an adjusting query concerning the uncertainty in the comparison: what is the probability of the priority ratio being between the best guess ± 1 unit of the pairwise comparison scale? An application of the method is presented in the form of multiple-criteria evaluation of alternative management plans for a forest area.
  • Leskinen, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: pekka.leskinen@metla.fi (email)
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jk@nn.fi

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