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A fuzzy multi-criteria group decision making framework for evaluating health-care waste disposal alternatives

Authors :
Dursun, Mehtap
Karsak, E. Ertugrul
Karadayi, Melis Almula
Source :
Expert Systems with Applications. Sep2011, Vol. 38 Issue 9, p11453-11462. 10p.
Publication Year :
2011

Abstract

Abstract: Nowadays, as in all other organizations, the amount of waste generated in the health-care institutions is rising due to their extent of service. Medical waste management is a common problem of developing countries including Turkey, which are becoming increasingly conscious that health-care wastes require special treatment. Accordingly, one of the most important problems encountered in Istanbul, the most crowded metropolis of Turkey, is the disposal of health-care waste (HCW) from health-care institutions. Evaluating HCW disposal alternatives, which considers the need to trade-off multiple conflicting criteria with the involvement of a group of experts, is a highly important multi-criteria group decision making problem. The inherent imprecision and vagueness in criteria values concerning HCW disposal alternatives justify the use of fuzzy set theory. This paper presents a fuzzy multi-criteria group decision making framework based on the principles of fuzzy measure and fuzzy integral for evaluating HCW treatment alternatives for Istanbul. In group decision making problems, aggregation of expert opinions is essential for properly conducting the evaluation process. In this study, the ordered weighted averaging (OWA) operator is used to aggregate decision makers’ opinions. Economic, technical, environmental and social criteria and their related sub-criteria are employed to assess HCW treatment alternatives, namely “incineration”, “steam sterilization”, “microwave”, and “landfill”. A comparative analysis is presented using another classical operator to aggregate decision makers’ preferences. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09574174
Volume :
38
Issue :
9
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
60379876
Full Text :
https://doi.org/10.1016/j.eswa.2011.03.019