OBTAINING MINIMUM VARIABILITY OWA OPERATORS UNDER A FUZZY LEVEL OF ORNESS

Kaj-Mikael Björk

Abstract

Finding the optimal OWA (ordered weighted averaging) operators is important in many decision support problems. The OWA-operators enables the decision maker to model very different kinds of aggregator operators. The weights need to be, however, determined under some criteria, and can be found through the solution of some optimization problems. The important parameter called the level of orness may, in many cases, be uncertain to some degree. Decision makers are often able to estimate the level using fuzzy numbers. Therefore, this paper contributes to the current state of the art in OWA operators with a model that can determine the optimal (minimum variability) OWA operators under a (unsymmetrical triangular) fuzzy level of orness.

References

  1. Carlsson C, Fuller R. & Majlender P., 2003. A note on constrained OWA aggregation. Fuzzy sets and systems, 139, pp. 543-546.
  2. Chang H-C., 2004. An application of fuzzy sets theory to the EOQ model with imperfect quality items. Computers & Operations Research, 31, pp. 2079- 2092.
  3. Fuller R. & Majlender P., 2001. An analytical approach for obtaining OWA-operator weights. Fuzzy sets and systems, 124, pp. 53-57.
  4. Fuller R. & Majlender P., 2003. On obtaining minimum variability OWA operator weights. Fuzzy sets and systems, 136, pp. 203-215.
  5. O'Hagan M., 1988. Aggregating template or rule antecedents in real-time expert systems with fuzzy set logic. Proceedings of 22nd annual Asilomal conference on signals, systems and computers, pp. 681-689.
  6. Salameh M.K. and Jaber M.Y., 2000. Economic production quantity model for items with imperfect quality. Int. Journal of Production Economics, 64, pp.59-64.
  7. Yager R.R., 1988. Ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 18, pp. 183-190.
  8. Yao J.S. and Wu K., 2000. Ranking fuzzy numbers based on decomposition principle and signed distance, Fuzzy Sets and Systems, 116, pp. 275-288.
  9. Yao J-S and Chiang J., 2003. Inventory without backorder with fuzzy total cost and fuzzy storing cost defuzzified by centroid and signed distance. European Journal of Operational Research, 148, pp. 401-409.
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Paper Citation


in Harvard Style

Björk K. (2008). OBTAINING MINIMUM VARIABILITY OWA OPERATORS UNDER A FUZZY LEVEL OF ORNESS . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8111-30-2, pages 114-119. DOI: 10.5220/0001483501140119


in Bibtex Style

@conference{icinco08,
author={Kaj-Mikael Björk},
title={OBTAINING MINIMUM VARIABILITY OWA OPERATORS UNDER A FUZZY LEVEL OF ORNESS},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2008},
pages={114-119},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001483501140119},
isbn={978-989-8111-30-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - OBTAINING MINIMUM VARIABILITY OWA OPERATORS UNDER A FUZZY LEVEL OF ORNESS
SN - 978-989-8111-30-2
AU - Björk K.
PY - 2008
SP - 114
EP - 119
DO - 10.5220/0001483501140119