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GISwaps: A New Method for Decision Making in Continuous Choice Models Based on Even Swaps

GISwaps: A New Method for Decision Making in Continuous Choice Models Based on Even Swaps

Goran Milutinovic, Ulla Ahonen-Jonnarth, Stefan Seipel
Copyright: © 2018 |Volume: 10 |Issue: 3 |Pages: 22
ISSN: 1941-6296|EISSN: 1941-630X|EISBN13: 9781522543886|DOI: 10.4018/IJDSST.2018070104
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MLA

Milutinovic, Goran, et al. "GISwaps: A New Method for Decision Making in Continuous Choice Models Based on Even Swaps." IJDSST vol.10, no.3 2018: pp.57-78. http://doi.org/10.4018/IJDSST.2018070104

APA

Milutinovic, G., Ahonen-Jonnarth, U., & Seipel, S. (2018). GISwaps: A New Method for Decision Making in Continuous Choice Models Based on Even Swaps. International Journal of Decision Support System Technology (IJDSST), 10(3), 57-78. http://doi.org/10.4018/IJDSST.2018070104

Chicago

Milutinovic, Goran, Ulla Ahonen-Jonnarth, and Stefan Seipel. "GISwaps: A New Method for Decision Making in Continuous Choice Models Based on Even Swaps," International Journal of Decision Support System Technology (IJDSST) 10, no.3: 57-78. http://doi.org/10.4018/IJDSST.2018070104

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Abstract

This article describes how continuous GIS-MCDM problems are commonly managed by combining some weighting method based on pairwise comparisons of criteria with an aggregation method. The reliability of this approach may be questioned, though. First, assigning weights to criteria, without taking into consideration the actual consequences or values of the alternatives, is in itself controversial. Second, the value functions obtained by this approach are in most cases linear, which is seldom the case in reality. The authors present a new method for GIS-MCDM in continuous choice models based on Even Swaps. The method is intuitive and easy to use, based on value trade-offs, and thus not relying on criteria weighting. Value functions obtained when using the method may be linear or non-linear, and thereby are more sensitive to the characteristics of the decision space. The performed case study showed promising results regarding the reliability of the method in GIS-MCDM context.