Decision Support for Forest Management

ISBN-13: 9783319235219 / Angielski / Twarda / 2015 / 307 str.

Annika Kangas; Mikko Kurttila; Teppo Hujala

Opis

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.

Recenzje

"This book is based on the research, lectures and real-life experiences of authors who all originate from Finland. ...  This book presents the advances and progress in the use of OR in forestry management over the last forty to fifty years. The substantial growth in the range of techniques, methods and approaches extensively shown through examples in the book Decision Support for Forest Management, should put forest managers and decision makers well equipped to face this challenge." (Hans W. Ittmann, IFORS News, Vol. 11 (1), March, 2017)

Spis treści

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.

Blurb

This book offers a thorough review and explanation of decision support methods and tools, and shows how these are best applied to a wide range of situations in the practice of sustainable forest management. The goal is to provide both students and working forest managers a toolbox of methods covering most of the decision situations encountered in practice.

 

The first chapter introduces basic concepts of planning, decision making and decision support. Chapter Two explores forest management as a planning problem, including definitions of sustainability, the development of approaches to optimisation; approaches to multi-criteria decisions; and the need for participatory planning. The third chapter covers single-criteria problems, showing how to measure utility and value, how to assess risk, and how to estimate a value function. A chapter on multi-criteria problems delves deeply into decision modelling, utility functions including SMART and TOPSIS, Analytic Hierarchy Process and more. Chapter Five addresses uncertainty in multi-criteria decision making, introducing fuzzy set theory, outranking methods such as PROMETHEE and ELECTRE, and probabilistic uncertainty using Stochastic Multicriteria Acceptability Analysis (SMAA). Chapter Six discusses linear programming and its extensions in forest planning. Chapters Seven and Eight go deeper still, discussing heuristic optimisation and uncertainty in optimisation. Chapter Nine address group decision making and participatory planning, including the roles of decision makers, stakeholders and facilitators. Chapter Ten addresses voting as a group decision making tool. Chapter Eleven examines participatory planning processes in action, as applied to specific contexts in forest management planning. Chapter Twelve is devoted to behavioural aspects of planning, decision making and participation, including concepts as ‘satisficing’ or ´groupthink’.

The concluding chapter offers the authors’ insights on how all these concepts, tools and practices reflect the three worlds: material, personal and social.

 

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.