Comparison of Fuzzy Multiple Attribute Group Decision Making Methods for Ranking Water Transfer Projects

Document Type : Original Article

Authors

1 Ph.D. candidate, Department of water structures, College of Agriculture, University of Tarbiat Modares, Tehran, Iran

2 Professor, Department of water structures, College of Agriculture, University of Tarbiat Modares, Tehran, Iran

3 M.Sc. Environment and Water Research Center, Ministry of energy, Tehran, Iran

Abstract

Water resources are among basics for sustainable development. The non uniform temporal and spatial distribution of water resources is led to shortage water in arid and semi arid regions. The inter basin water transfer projects are one remedy to this problem. According to the diversity of the feasible water transfer projects, ranking of the projects with different criteria is currently one of the important issues in water resources management. Fuzzy Multiple Criteria Decision Making (FMADM) is a collection of methodologies which can be used to compare, select, or rank multiple alternatives that typically involve incommensurate attributes. The aim of this research was to use some of the fuzzy multiple attribute group decision making methods for ranking some inter-basin water transfer projects of Karoon River, western Iran. Maximizing and minimizing sets method, the Bonissone’s method for group decision making, Fuzzy TOPSIS for group decision making, and Fuzzy Decision Making software were used in this study. A set of 10 inter-basin water transfer projects with 8 criteria were considered. First, the weight of each criterion was determined within a group of five water resources experts, Then the rating preference for each alternative were obtained by the same group of experts.  Finally, the results of different methods were compared. The results showed that the Tunnel Koohrang 1 posses the higher rank. Also, the Spearman rank correlation coefficient was obtained between different methods. The results showed that the Fuzzy TOPSIS and Bonissone method provide the best correlation. For evaluating the criteria weightings, the sensitivity analysis was conducted and the results were compared.

Keywords

References

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History

  • Receive Date: 19 December 2008
  • Accept Date: 28 September 2011

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