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An Introductory Overview to Multi Criteria Evaluation

An Introductory Overview to Multi Criteria Evaluation . GEOG 5161: Research Design Professor Kenneth E. Foote Petra Norlund 2010. Outline. Introduction and Background Definitions What is multi criteria evaluation? How and when is it useful?

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An Introductory Overview to Multi Criteria Evaluation

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  1. An Introductory Overview to Multi Criteria Evaluation GEOG 5161: Research Design Professor Kenneth E. Foote Petra Norlund 2010

  2. Outline • Introduction and Background • Definitions • What is multi criteria evaluation? • How and when is it useful? • How does it work? Case study to show how it is implemented • Pros and cons of the method. • Why should we use it?

  3. Kärt barn har många namn... Multi Criteria Analysis Multi Criteria Evaluation (MCE) Multi Criteria Preference Analysis Multi Criteria Decision Making Multi Objective Evaluation These methods are essentially one and the same! MCE = Multi-criteria evaluation is primarily concerned with how to combine the information from several criteria to form a single index of evaluation

  4. Introduction • Land is a scarce resource: • Identifying suitability for • Where to build a dam • Water flow • Mountainous? • Where to place a hospital • Costs • Access • Greatest need • Criteria can be based on human or physical geography factors

  5. Background • Early methods (pre computers): • Ian McHarg (1969) Design with Nature • Used for suitability analysis • Tracing paper overlays • Limited to simple Boolean analysis: AND, OR, NOT See demo!

  6. Post computers: Basic GIS Approaches • Polygon overlay (Boolean logic) Example uses: • Nuclear waste disposal sites • Street routing

  7. Definitions • Decisions: a choice between alternatives • Criterion: some basis for a decision. Two main classes: • Factor: enhances or detracts from the suitability of a land use alternative (e.g. distance from a road) • Constraint: limits the alternatives • Goal or target: some characteristic that the solution must possess (a positive constraint)

  8. The Basics

  9. What is it used for? • Decision making • Dispute resolution • Water resource management • Sustainable development • etc

  10. Principles of MCE • Methodology: • Determine criteria (factors/constraints) to be included • Determining the weights for each factor • Sensitivity analysis of results

  11. 1st Step: Determine the criteria to be included • Criteria determine the alternatives • Oversimplification of the decision problem could lead to too few criteria being used • Using a large number of criteria reduces the influence of any one criteria • Often proxies must be used since the criteria of interest may not be determinable

  12. Example: Case study of a suitable dam and reservoir site • Criteria used: • River • Urban • Forest • Accumulated water flow • Existing reservoir • Watershed boundary • City • Hydraulic head • Undulation

  13. Determine the weights • A decision is the result of a comparison of one or more alternatives with respect to one or more criteria that we consider relevant for the task at hand. • Among the relevant criteria we consider some as more important and some as less important; this is equivalent to assigning weights to the criterion according to their relative importance.

  14. 2nd stage, assigning weights

  15. Weights assigned using AHP

  16. Weights assigned using the Rank Order method

  17. Sensitivity analysis • → sensitivity analysis: vary the scores/weights of the factors to determine the sensitivity of the solution to minor changes • Choice of criteria (e.g. why included?) • Assesses the reliability of data: how stable is the final result? • Choice for weighting factors is subjective • Will the overall solution change if you use other weighing factors?

  18. MCE – pros and cons • Cons: • Dynamic problems strongly simplified into a linear model • Static, lacks the time dimension • Controversial method – too subjective? • Pros: • Gives a structured and traceable analysis. • Possibility to use different evaluation factors makes it a good tool for discussion. • Copes with large amounts of information. • It works!

  19. Conclusion • Good for any complex decision problem. • Allows decision makers to show their thinking. • Useful in any GIS analysis where several criteria are incorporated. • Includes the ability to weigh criteria. • Often used for land allocation.

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