Decision support for forest management
著者
書誌事項
Decision support for forest management
（Managing forest ecosystems, v. 16）
Springer, c2008
- : hard
- : ebook
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book has been developed as a textbook of decision support methods for s- dents and can also serve as a handbook for practical foresters. It is based on the research we have carried out and lectures we have given over the past years. We have set out to present all the methods in enough details and examples that they can be adopted from this book. For researchers who need more details, references are given to more advanced scienti c papers and books. In this book, theories of decision making and the methods used for forestry - cision support are presented. The book covers basics of classical utility theory and its fuzzy counterparts, exact and heuristic optimization method and modern mul- criteria decision support tools such as AHP or ELECTRE. Possibilities of analyzing and dealing with uncertainty are also brie y presented. The use of each method is illustrated with examples. In addition to decision aid methods, we present the basic theory of participatory planning. Both hard and soft methods suitable for partici- tory or group decision analysis are presented, such as problem structuring method and voting. The criticism towards decision theory is also covered.
Finally, some real-life examples of the methods are presented. Annika Kangas Department of Forest Resource Management University of Helsinki Jyrki Kangas Metsahallitus .. Mikko Kurttila University of Joensuu v Acknowledgements Manyresearchersandstudentshavehelpedusbyreviewingchapters,suggesting- provements and even checking our example calculations. We would like to ackno- edgethesereviewers,Ms.AnuHankala,M.Sc.TeppoHujala,M.Sc.AnnuKaila,Dr.
目次
Preface. Acknowledgements. 1. Introduction. 1.1 Planning and decision support. 1.2 Forest management planning. 1.3 History of forest planning.- Discrete problems. 2. Unidimensional problems. 2.1 Decisions under risk and uncertainty. 2.2 Measuring utility and value. 2.2.1 Estimating a utility function. 2.2.2 Estimating a value function.- 3. Multi-criteria decision problems. 3.1 Theoretical aspects. 3.2 Multi-attribute utility functions. 3.2.1 Function forms. 3.2.2 Basis for estimating the weights. 3.2.3 SMART. 3.3 Even Swaps. 3.4 Analytic hierarchy process. 3.4.1 Decision problem. 3.4.2 Phases of AHP. 3.4.3 Uncertainty in AHP. 3.4.4 ANP. 3.5 A'WOT.- 4. Uncertainty in multi-criteria decision making. 4.1 Nature of uncertainty. 4.2 Fuzzy set theory. 4.2.1 Membership functions and fuzzy numbers. 4.2.2 Fuzzy goals in decision making. 4.2.3 Fuzzy additive weighting. 4.3 Possibility theory in decision making. 4.4 Evidence theory. 4.5 Outranking methods. 4.5.1 Outline. 4.5.2 PROMETHEE method. 4.5.3 ELECTRE method. 4.5.4 Other outranking methods. 4.6 Probabilistic uncertainty in decision analysis. 4.6.1 Stochastic multicriteria acceptability analysis (SMAA). 4.6.2 SMAA-O. 4.6.3 Pairwise probabilities.- Continuous problems. 5. Optimization. 5.1 Linear programming. 5.1.1 Primal problem. 5.1.2 Dual problem. 5.1.3 Forest planning problem with several stands. 5.1.4 JLP software. 5.2 Goal programming. 5.3 Integer programming. 5.4 Uncertainty in optimization. 5.5 Robust portfolio modelling. 5.5.1 Principles of the method. 5.5.2 Use of RPM in forest planning.- 6. Heuristic optimization. 6.1 Principles. 6.2 Objective function forms. 6.3 HERO. 6.4 Simulated annealing and threshold accepting. 6.5 Tabu search. 6.6 Genetic algorithms. 6.7 Improving the heuristic search. 6.7.1 Parameters of heuristic optimisation techniques. 6.7.2 Expanding the neighbourhood. 6.7.3 Combining optimisation techniques.- Cases with several decision makers. 7. Group decision making and participatory planning. 7.1 Decision makers and stakeholders. 7.2 Public participation process. 7.2.1 Types of participation process. 7.2.2 Success of the participation process. 7.2.3 Defining the appropriate process. 7.3 Tools for eliciting the public preferences. 7.3.1 Surveys. 7.3.2 Public hearings. 7.4 Problem structuring methods. 7.4.1 Background. 7.4.2 Strategic options development and analysis (SODA). 7.4.3 Soft systems methodology (SSM). 7.5 Decision support for group decision making.- 8. Voting methods. 8.1 Social choice theory. 8.1.1 Outline. 8.1.2 Evaluation criteria for voting systems. 8.2 Positional voting schemes. 8.2.1 Plurality voting. 8.2.2 Approval voting. 8.2.3 Borda count. 8.3 Pairwise voting. 8.4 Fuzzy voting. 8.5 Probability voting. 8.6 Multicriteria approval. 8.6.1 Original method. 8.6.2 Fuzzy MA. 8.6.3 Multicriteria approval voting.- Application viewpoints. 9. Behavioural aspects. 9.1 Criticism towards decision theory. 9.1.1 Outline. 9.1.2 Satisficing or maximizing?. 9.1.3 Rules or rational behaviour?. 9.2 Image theory. 9.3 Prospect theory.- 10. Practical examples of using MCDS methods. 10.1 Landscape ecological planning. 10.2 Participatory planning. 10.3 Spatial objectives and heuristic optimisation in practical forest planning.- 11. Final remarks.-
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