Buch, Englisch, 307 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 493 g
Reihe: Managing Forest Ecosystems
Buch, Englisch, 307 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 493 g
Reihe: Managing Forest Ecosystems
ISBN: 978-3-319-33101-0
Verlag: Springer
This updated and expanded second edition adds the most recent advances in participatory planning approaches and methods, giving special emphasis to decision support tools usable under uncertainty. The new edition places emphasis on the selection of criteria and creating alternatives in practical multi-criteria decision making problems.
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Planning and Decision Support.- 1.1. What Is Planning?- 1.2. Phases of Decision Making.- 1.3. Classification of Planning Problems.- References.- 2. Forest Management Planning.- 2.1. Forest Management as a Planning Problem.- 2.2. Stand-Level Forest Planning.- 2.3 Development of Sustainable Forest Management Planning Approaches.- 2.3.1 Definitions of Sustainability.- 2.3.2 Fully Regulated Forestry.- 2.3.3 Development Of Optimisation Approaches.- 2.3.4 Development Of Multi-Criteria Approaches.- 2.3.5 Need For Participatory Planning.- References.- 3. Single-Criteria Problems.- 3.1. Decisions Under Risk and Uncertainty.- 3.2. Measuring Utility and Value.- 3.2.1 Estimating a Utility Function.- 3.2.2 Risk Attitude.- 3.2.3 Estimating a Value Function.- References.- 4. Multi-Criteria Decision Problems.- 4.1. Decision Model.- 4.1.1. Objectives and Decision Criteria.- 4.1.2 Selecting the Set of Criteria.- 4.1.3 Designing Alternatives.- 4.1.4 Indifference, Preference and Tradeoff.- 4.1.5 Dominance.- 4.2. Multi-Attribute Utility Functions.- 4.2.1 Function Forms.- 4.2.2 Basis For Estimating The Weights.- 4.2.3 SMART.- 4.2.4 TOPSIS.- 4.2.5 Cautionary Note of Weighting Methods.- 4.3. Analytic Hierarchy Process.- 4.3.1 Decision Problem.- 4.3.2 Phases of AHP.- 4.3.3 Uncertainty in AHP.- 4.4. ANP.- 4.5. Even Swaps.- 4.6. A'WOT.- References.- 5. Uncertainty in Multi-Criteria Decision Making.- 5.1. Nature of Uncertainty.- 5.2. Fuzzy Set Theory.- 5.2.1 Membership Functions and Fuzzy Numbers.- 5.2.2. Fuzzy Goals in Decision Making.- 5.2.3. Fuzzy Additive Weighting.- 5.3. Outranking Methods.- 5.3.1. Outline.- 5.3.2 PROMETHEE Method.- 5.3.3 ELECTRE Method.- 5.3.4. Other Outranking Methods.- 5.4. Probabilistic Uncertainty in Decision Analysis.- 5.4.1 Stochastic Multicriteria Acceptability Analysis (SMAA).- 5.4.2 SMAA-O.- 5.4.3 Pairwise Probabilities.- References.- 6. Linear Programming and its Extensions in Forest Planning.- 6.1. Linear Programming.- 6.1.1 Primal Problem.- 6.1.2 Dual Problem.- 6.2. Forest Planning with LP.- 6.2.1 Formulating a Problem in an Estate Level.- 6.2.2 Even Flow Constraints.- 6.2.3 Production Possibility Frontier.- 6.3. Goal Programming.- 6.2.1 Soft Constraints.- 6.2.2 Balancing Different Goals.- 6.4. General Forest Planning Formulation.- 6.5. Integer Programming.- 6.6. Hierarchical Forest Planning.- 6.7 Spatial Goals and Constraints in Linear Programming.- 6.7.1 Adjacency Constraints and Green-Up Constraints.- 6.7.2 Spatial Goals Suitable for Linear Programming.- References.- 7. Heuristic Optimisation.- 7.1 Principles Of Heuristic Optimisation.- 7.1.1 Definitions.- 7.1.2 Objective Function Forms.- 7.2 HERO.- 7.3. Metaheuristic Methods Using Local Improvements.- 7.3.1 Simulated Annealing And Threshold Accepting.- 7.3.2 Tabu Search.- 7.3.3 Defining the Parameters.- 7.3.4 Defining the Neighborhood.- 7.4. Population Based Methods.- 7.4.1 Genetic Algorithm.- 7.4.2 Other Population-Based Methods.- 7.5. Local/Global Methods.- 7.5.1 Cellular Automaton.- 7.5.2 Reduced Cost Approach.- 7.6. Combining Optimisation Techniques.- References.- 8. Uncertainty in Optimisation.- 8.1. Stochastic Programming.- 8.1.1 Effect of Uncertainty on Optimisation.- 8.1.2 Basics of Stochastic Programming.- 8.1.3 Modeling Forest Planning Problems with Stochastic Programming.- 8.1.4 Value of Information and Stochastic Solution.- 8.1.5 Two-Stage Stochastic Programming.- 8.2. Robust Programming.- 8.3. Chance-Constrained Programming.- 8.4. Robust Portfolio Modeling.- 8.4.1 Principles of the Method.- 8.4.2 Use of RPM in Forest Planning.- References.- 9. Participatory Planning and Group Decision Making.- 9.1. Decision Makers and Stakeholders.- 9.2. Designing the Appropriate Process.- 9.3 Facilitation and Different Facilitator’s Roles.- 9.4. Success of the Participation Process.- References.- 10. Voting Methods.- 10.1. Social Choice Theory.- 10.1.1 Outline.- 10.1.2. Evaluation Criteria for Voting Systems.- 10.2. Positional Voting Schemes.- 10.2.1. Plurality Voting.- 10.2.2. Approval Voting.- 10.2.3. Borda Count.- 10.3. Pairwise Voting.- 10.4. Fuzzy Voting.- 10.5. Probability Voting.- 10.6. Multicriteria Approval.- 10.6.1 Original Method.- 10.6.2 Fuzzy MA.- 10.6.3. Multicriteria Approval Voting.- References.- 11. Participatory Planning Processes in Action.- 11.1. Participatory Planning Case Types.- 11.1.1 Participation in Public Urban Forests.- 11.1.2 Regional Forest Planning.- 11.1.3. Preparation of Policy Programmes.- 11.2 Problem Structuring Methods.- 11.2.1. Background.- 11.2.2. Strategic Options Development And Analysis (SODA).- 11.2.3. Soft Systems Methodology (SSM) .- 11.2.4. Strategic Choice Approach (SCA) .- 11.3. Tools for Eliciting the Public Preferences.- 11.3.1. Surveys, Panel Barometers and Interviews.- 11.3.2 Public Hearings and Workshops.- 11.3.3 Location Specific Preferences.- 11.4. Decision Support for Group Decision Making.- 11.4.1 Combined Use of MCA Methods in Group Settings.- 11.4.2 Utilizing GDSS Software for Distributed Group Negotiation.- References.- 12. Behavioral Aspects.- 12.1 Criticism Towards Decision Theory.- 12.1.1 Outline.- 12.1.2. Satisficing or Maximizing?- 12.1.3. Rules or Rational Behavior?- 12.2. Image Theory.- 12.3 Biases and Distortions in Decision Support Situations.- References.- 13. Final Remarks.- References.
