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Applying Stochastic Multicriteria Acceptability Analysis to Forest Ecosystem Management with Both Cardinal and Ordinal Criteria

Jyrki Kangas, Joonas Hokkanen, Annika Kangas, Risto Lahdelma, Pekka Salminen, Applying Stochastic Multicriteria Acceptability Analysis to Forest Ecosystem Management with Both Cardinal and Ordinal Criteria. Forest Science (49), 928–937, 2003.

Abstract:

Multicriteria decision analysis is applied to ecosystem management
planning in a forest landscape. Ten alternative action plans were
evaluated employing five criteria. For some criteria, cardinal measures
with their associated uncertainties were obtained. For other criteria,
only ordinal (ranking) information was available. The Stochastic
Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O)
method was used, as it accommodates both cardinal and ordinal data. This
is the first application of SMAA methods to forest management. SMAA-O
represents inaccurate or uncertain cardinal criteria measurements by a
joint probability distribution. Ordinal data is converted into stochastic
cardinal data by simulating mappings between ordinal and cardinal scales
that preserve the given rankings. At the same time, the unknown or partly
known preferences of the decision maker are simulated by choosing weights
randomly from appropriate distributions. The main results of the analysis
are “acceptability indices” that describe the variety of different
weights that support an alternative for a given rank. The special
characteristics of SMAA-O are best utilized in problems involving
uncertainty and where both cardinal and ordinal data are to be employed.
It also serves well as an analysis tool in interactive planning
processes, especially when criteria weights are not known or they are
difficult to assess.

BibTeX entry:

@ARTICLE{jKaHoKaLaSa03a,
  title = {Applying Stochastic Multicriteria Acceptability Analysis to Forest Ecosystem Management with Both Cardinal and Ordinal Criteria},
  author = {Kangas, Jyrki and Hokkanen, Joonas and Kangas, Annika and Lahdelma, Risto and Salminen, Pekka},
  journal = {Forest Science},
  number = {49},
  pages = {928–937},
  year = {2003},
  keywords = {Decision analysis, forest planning, landscape ecology, multicriteria decision support, sustainable forestry},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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