Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances

Pasi Luukka, Mario Fedrizzi, Leoncie Niyigena, Mikael Collan

2013

Abstract

This article introduces a new extension to fuzzy similarity based fuzzy TOPSIS that uses multi-distance in aggregation. OWA-based multi-distances are used in the aggregation process. For the weight generation in OWA the O'Hagan's method is used to find optimal weights. Several different, predefined orness values were tested. The presented method is applied to a project selection problem.

Paper Citation

in Harvard Style

Luukka P., Fedrizzi M., Niyigena L. and Collan M. (2013). Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances . In Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 193-200. DOI: 10.5220/0004552601930200

in Bibtex Style

@conference{fcta13,
author={Pasi Luukka and Mario Fedrizzi and Leoncie Niyigena and Mikael Collan},
title={Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2013)},
year={2013},
pages={193-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004552601930200},
isbn={978-989-8565-77-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2013)
TI - Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances
SN - 978-989-8565-77-8
AU - Luukka P.
AU - Fedrizzi M.
AU - Niyigena L.
AU - Collan M.
PY - 2013
SP - 193
EP - 200
DO - 10.5220/0004552601930200