Introduction to Multi-Objective Forest Planning

Published Date

Volume 6 of the series Managing Forest Ecosystems pp 1-19

Title 

Introduction to Multi-Objective Forest Planning

• Author 

• Timo Pukkala

Abstract

The purpose of forest planning is to support forestry decision-making by suggesting management alternatives, providing information about their consequences, and helping the decision maker to rank the alternatives. In multi-objective forest planning, forest plans are evaluated using various multiple criteria decision support methods and multi-objective optimisation algorithms. Multiple criteria comparison methods help to systematise subjective evaluations whereas multi; objective optimisation seeks the best plan among a huge number of alternatives using automated computer-based search methods. The ranking of alternatives depends on the preferences of the decision maker, both in multiple criteria comparison and in multi-objective optimisation. A careful analysis of preferences is an important step of any multi-objective planning case. The quantitative approach to decision-making suggests that a specific planning model be developed for every planning situation. This model is then solved, the result being a candidate plan that must pass various post-optimisation tests and analyses. There are several ways to prepare a multi-objective planning model, based on linear programming, goal programming, penalty functions or multi-attribute utility theory. The planning model may be solved using mathematical programming techniques or various heuristics. The use of heuristic optimisation has gained popularity in forest planning along the increasing importance of ecological forest management goals, which are often described with spatial variables. Examples of heuristics available to multi-objective forest planning are random ascent heuristics, simulated annealing, tabu search and genetic algorithm. Practical forest plans are produced in a computerised system, which includes subsystems for data management, simulation of stand development, planning model generation and optimisation, and subjective evaluation of alternative plans.

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Measurement of Preferences in Multiple Criteria Evaluation

Published Date

Volume 6 of the series Managing Forest Ecosystems pp 21-36

Title 

Measurement of Preferences in Multiple Criteria Evaluation

• Author 

•  Juha M. Alho
• , Pekka Korhonen
• , Pekka Leskinen

Abstract

In this paper, we deal with the problem of modelling preferences in multiple criteria evaluation situations. When the number of objects to be evaluated is small, then it is possible to make a detailed analysis of the decision-maker’s preferences to find out a “value” or a “score” for each object. For example, in the Analytic Hierarchy Process, preference analysis is based on pairwise comparisons. We consider the statistical analysis of pairwise comparisons, and show that several issues of measurement scale must be clearly understood, before one can reliably apply the methods in practice. Our approach is based on the use of regression analysis rather than the eigenvalue technique of the AHP, to find the value scores for alternatives.

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Multiple Criteria Decision Support Methods in Forest Management

Published Date

Volume 6 of the series Managing Forest Ecosystems pp 37-70

Title 

Multiple Criteria Decision Support Methods in Forest Management

An overview and comparative analyses

• Author 

• Jyrki Kangas
• , Annika Kangas

Abstract

Nowadays, forests are often managed for multiple uses. Forests are expected to produce reasonable incomes while at the same time promoting nature conservation and amenity values. There are also other characteristics that make natural resources decisionmaking situations complex. For example, group decision making and public participation are often required. To help decision makers make good choices, information and analyses are needed on the decision situation, on alternative choices of action, and on the consequences of alternative choices as well as on the preferences among these consequences. Multiple Criteria Decision Support (MCDS) methods are decision analysis tools that have been developed for dealing with all that information in order to support complex decision making with multiple objectives. In this chapter, some MCDS methods that recently have been applied to forestry or other natural resources management planning problems, and have been found to be promising, will be presented. In addition, some forestry applications are briefly described, and experiences gained using MCDS methods in forest management are discussed. Of the MCDS approaches, a closer look is taken at the Analytic Hierarchy Process, outranking methods, voting approaches, and the Stochastic Multicriteria Acceptability Analysis, because of their potentials for application. Applications for practically all MCDS methods with different qualities can be found in the field of natural resources decision support. However, no single method is best for all the decision support processes. The tool to be used should be chosen to fit the situation at hand: i.e., planning-case-wise consideration is always needed in order to build up an appropriate decision support process.

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