Fuzzy multicriteria disposal method and site selection for municipal solid waste

Ekmekcioglu M., Kaya T., KAHRAMAN C.

WASTE MANAGEMENT, vol.30, pp.1729-1736, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30
  • Publication Date: 2010
  • Doi Number: 10.1016/j.wasman.2010.02.031
  • Journal Name: WASTE MANAGEMENT
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1729-1736
  • Istanbul Technical University Affiliated: Yes


The use of fuzzy multiple criteria analysis (MCA) in solid waste management has the advantage of rendering subjective and implicit decision making more objective and analytical, with its ability to accommodate both quantitative and qualitative data. In this paper a modified fuzzy TOPSIS methodology is proposed for the selection of appropriate disposal method and site for municipal solid waste (MSW). Our method is superior to existing methods since it has capability of representing vague qualitative data and presenting all possible results with different degrees of membership. In the first stage of the proposed methodology, a set of criteria of cost, reliability, feasibility, pollution and emission levels, waste and energy recovery is optimized to determine the best MSW disposal method. Landfilling, composting, conventional incineration, and refuse-derived fuel (RDF) combustion are the alternatives considered. The weights of the selection criteria are determined by fuzzy pairwise comparison matrices of Analytic Hierarchy Process (AHP). It is found that RDF combustion is the best disposal method alternative for Istanbul. In the second stage, the same methodology is used to determine the optimum RDF combustion plant location using adjacent land use, climate, road access and cost as the criteria. The results of this study illustrate the importance of the weights on the various factors in deciding the optimized location, with the best site located in catalca. A sensitivity analysis is also conducted to monitor how sensitive our model is to changes in the various criteria weights. (C) 2010 Elsevier Ltd. All rights reserved.