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Locating a Waste Treatment Facility by Using Stochastic Multicriteria Acceptability Analysis with Ordinal Criteria

Risto Lahdelma, Pekka Salminen, Joonas Hokkanen, Locating a Waste Treatment Facility by Using Stochastic Multicriteria Acceptability Analysis with Ordinal Criteria. European Journal of Operational Research 142(2), 345–356, 2002.

Abstract:

In this paper we describe a real-life application of an ordinal multicriteria method in the context of choosing a location
for a waste treatment facility near Lappeenranta in South-Eastern Finland. The associated environmental
impact assessment (EIA) procedure is briefly described. The application was characterized by two interesting properties:
no preference information was available, and only ordinal measurements for the criteria were available.
The large amount of data obtained was then analyzed using the SMAA-O method - Stochastic Multicriteria Acceptability
Analysis with Ordinal criteria designed for this problem setting. SMAA-O converts ordinal information
into cardinal data by simulating all possible mappings between ordinal and cardinal scales that preserve the given
rankings. As with the basic SMAA-method, the decision makers' (DMs') unknown or partly known preferences
are at the same time simulated by choosing weights randomly from appropriate distributions. The main results of
the analysis are acceptability indices for alternatives describing the variety of preferences that could make each
alternative the best choice. Based on these and additional considerations, the DMs' made the final choice for the
location of the plant.

BibTeX entry:

@ARTICLE{jLaSaHo02a,
  title = {Locating a Waste Treatment Facility by Using Stochastic Multicriteria Acceptability Analysis with Ordinal Criteria},
  author = {Lahdelma, Risto and Salminen, Pekka and Hokkanen, Joonas},
  journal = {European Journal of Operational Research},
  volume = {142(2)},
  pages = {345–356},
  year = {2002},
  keywords = {Multicriteria decision making, Group decision making, Environmental planning, Waste treatment, Acceptability analysis},
}

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

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