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MCDA in natural resources management PART I. Jouni Pykäläinen, D.Sc.(For.) Metsämonex Ltd. Contents. planning steps quantifying and non-quantifying planning approaches prior and interactive articulation of preferences applying explicit utility modelling in forest management planning

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mcda in natural resources management part i
MCDA in natural resources managementPART I

Jouni Pykäläinen, D.Sc.(For.)

Metsämonex Ltd

contents
Contents
  • planning steps
  • quantifying and non-quantifying planning approaches
  • prior and interactive articulation of preferences
  • applying explicit utility modelling in forest management planning
  • pros and cons of the introduced approach
  • example of interactive approach
  • computer based (CB) - MCDA; examples and exercises by using HIPRE -software
why mcda
Why MCDA?
  • even a single DM often has multiple goals in NRE -planning
  • in many cases, several participants - with equal or unequal decision authority
  • NRE-planning problems are often very complex
  • finding the best plan calls for effective techniques for determining the NRE management goals and comparing and evaluating the decision alternatives
  • -> multi-criteria decision analysis (MCDA) has become more and more popular in NRE planning
planning supporting decision making
Planning = supporting decision making
  • planning steps:
  • a) structuring the decision problem
  • b) assessing possible impacts of each decision alternative
  • c) determining preferences of the DM and other participants of planning (goal analysis)
  • d) comparing and evaluating decision alternatives
  • ---------------------------------------------------------------------
  • decision making (selection among alternative plans)
  • the order of the steps may vary
  • the steps may be repeated several times
  • the steps may be implemented even simultaneusly
characteristics of non quantifying planning approach
Characteristics of non-quantifying planning approach
  • many sided discussions and illustrations
  • collaborative learning is emphasized
  • DM’s and other planning participants’ goals are defined verbally or graphically
  • holistic evaluation of the alternatives
characteristics of quantifying planning approach
Characteristics of quantifying planning approach
  • goals for NRE-management defined numerically in so called utility models
  • problem solving (optimization) techniques set requirements for measuring goals and realization of them in different alternatives
  • optimization; utility is maximized by solving the utility model
utility models
Utility models
  • explicit utility functions
  • target-, constraint- aspiration- and acceptability levels for the criteria values
    • mathematical programming applications
    • restricting the amount of acceptable solutions interactively
    • simplifying utility function determination
optimization
Optimization
  • explicit utility functions
    • discrete cases: including the values of criteria produced by different alternatives to the utility function and calculating the results
    • in continuous cases (plenty of alternatives): heuristic optimization techniques
  • mathematical programming algorithms (e.g. Simplex algorithm)
prior articulation of preferences
Prior articulation of preferences
  • assumes, that a utility model, which directly results in an optimal plan, can be formulated in the first trial
  • straightforward process: defining the utility model and solving it
interactive articulation of preferences
Interactive articulation of preferences
  • the solution is gradually improved by alternating the steps of defining the utility model and solving it
  • process is continued until the DM is satisfied with the result
  • DM’s goals are an important output of the planning process
    • the DM learns his preferences in the specific planning case during the process
when is it wise to use interactive techniques
When is it wise to use interactive techniques?
  • in planning situations where it is too difficult to define the utility model in advance
    • NRE –management goals are fuzzy for the DM
    • production possibilities of the planning area #ARE# not known well enough in advance
    • effects of producing different goals on the resource #ARE# not known well enough in advance
    • difficulties in using and understanding the planning method and/or the planning interface; interactive approach offers good possibilities for practising the planning technique
hybrid approach of prior and interactive articulation of preferences
Hybrid approach of prior and interactive articulation of preferences
  • to reach a plan that fulfils the DM\'s goals in the best possible way, both prior and interactive articulation of preferences may be needed
  • promoting the DM’s understanding of the bases for the solutions and planning more generally, adequate prior articulation of preferences probably decreases the amount of iterations needed in the interactive step
  • -> increases the DM\'s trust in the method and prevents frustration
slide13
A quantitative approach of MCDA: applying explicit utility modelling in forest management planning (Utility analysis in this presentation)
  • the approach illustrates: how a #multi- criteria# decision should be made ?
  • goals and utilities offered by different alternatives measured explicitly on interval scale
  • methods using ordinal and qualitative scales may give the same alternative to be the best one and even the priority order may become the same
    • remarkable differences in further analysis possibilities and communicational aspects
planning steps in utility analysis
Planning steps in utility analysis
  • Formulation of the decision hierarchy
  • Defining sub-utility functions
  • Defining weights for the goals
  • Calculating the priorities for the alternatives
  • Sensitivity analysis
sub utility functions
Sub-utility functions

Criteria/sub-criteria have different

values in different alternatives

Sub-utility functions

transform values of

the criteria measured in their own units into subjective sub-utility

values [0-1].

defining forms of sub utility functions
Defining forms of sub-utility functions
  • paired comparisons
    • different scales available
  • direct numeric method
    • interpolation of intermediate values
  • graphic interfaces
  • SMART
defining weights for criteria and sub criteria
Defining weights for criteria and sub-criteria
  • paired comparisons
    • different scales available
  • direct numeric method
    • interpolation of intermediate values
  • graphic interfaces
calculating the total utilities produced by the alternatives
Calculating the total utilities produced by the alternatives
  • rescaled (weighted) sub-utilities are summed up

where ui(qi) is a sub-utility function for criteria i

qi is the value of criteria i

ai is the weight of criteria i

n is the number of criteria

slide21

Output

Total utility

criteria

including the participants in the utility model formulation
Including the participants in the utility model formulation
  • For example:
  • one common utility function for all participants produced through discussions and negotiations
  • own weights for the criteria/sub-criteria defined by different participants
  • own weights and sub-utility functions defined by different participants
  • some parts of the utility model can be formulated by experts
sensitivity analysis
Sensitivity analysis
  • effects of changing the weights of the criteria/sub-criteria
  • effects of changing the forms of the sub-utility functions
  • effects of changing the weights of the parties in cases of multiple participants
some pros of the introduced approach
Some pros of the introduced approach
  • explicit definition of the decision making principles; transparency
  • forces one to focus on essentials
  • possibilities to integrate expert knowledge into utility models
  • effective technical problem solving
  • possibilities to sensitivity analysis
some cons of the introduced approach
Some cons of the introduced approach
  • difficulties in measuring some of the criteria
    • risk that all important aspects are not included into the planning model
  • possible difficulties in understanding the planning method
    • requires time for educating the planning method for the planning participants
slide27

Non-quantifying vs. quantifying approach

  • a) planning problems often complex
  • b) there are also several goals which should be taken into account at the same time
  • c) quantifying the problem may be difficult or even impossible
  • d) different people have different ways to grasp and process information (learning styles)
  • a + b -> need for quantifying approaches
  • c + d -> need for non-quantifying approach
  • Best support for decisions is often attained by using both approaches in the same process and comparing and evaluating the results of them.
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