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Exploring multi-criteria decision strategies in GIS with linguistic quantifiers: an extension of the analytical network process using ordered weighted averaging operators
Faculty
Computer Science
Year:
2013
Type of Publication:
Article
Pages:
2455-2482
Authors:
Eldrandaly, Khalid A
DOI:
10.1080/13658816.2013.815356
Journal:
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE TAYLOR \& FRANCIS LTD
Volume:
27
Research Area:
Computer Science; Geography; Physical Geography; Information Science \& Library Science
ISSN
ISI:000326350400012
Keywords :
GIS, multi-criteria evaluation, ANP, OWA
Abstract:
Many real-world spatial planning and management problems give rise to a geographical information system (GIS)-based multi-criteria decision-making. Analytical network process (ANP) provides a comprehensive methodology for representing complex multi-criteria decision-making problems as a network of criteria and alternatives, where feedback and interdependence relationships may exist within and between all the criteria and alternatives. Experts' experiences are used to estimate relative magnitudes of tangible and intangible factors through paired comparisons in order to make rational and consistent decisions. However, the GIS-based ANP, an adoption of weighted linear aggregation rule, typically employed a high trade-off decision strategy and neglected other decision strategies. This paper develops a novel GIS-based multi-criteria evaluation (MCE) procedure by extending the ANP using fuzzy quantifiers-guided ordered weighted averaging (OWA) operators. This extension, which generalizes the aggregation process used in the ANP, would provide a generic powerful decision-making tool that allows decision-makers to define a decision strategy on a continuum between pessimistic (risk-averse) and optimistic (risk-taking) strategies. By changing the linguistic quantifiers, the GIS-based ANP-OWA can generate a wide range of decision strategies taking into accounts the level of risk the decision-makers wish to assume in their MCE. A land-use suitability analysis in a region of Saudi Arabia is presented to demonstrate the application of the proposed procedure.
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