An Application of Fuzzy TOPSIS Method for Plant Selection in Rangeland Improvement (Case Study: Boroujerd Rangeland, Lorestan Province, Iran)
الموضوعات :Ali Ariapour 1 , Farzad Veisanloo 2 , Marzieh Asgari 3
1 - Dept. of Natural Resources, Islamic Azad University, Boroujerd Branch,
2 - Dept. of Natural Resources, Islamic Azad University, Boroujerd Branch,
3 - Range Management, Islamic Azad University, Boroujerd Branch
الکلمات المفتاحية: fuzzy logic, Species selection, Multiple Criteria Decision Making MCDM, Fuzzy TOPSIS method,
ملخص المقالة :
Species selection based on a new method such as a fuzzy method is one of the most important stages in the successful plantation management planning as choosing a suitable species for the site can be the key to success. This paper is based on a fuzzy extension of the Technique or Order Preference which is similar to Ideal Solution (TOPSIS) method. The purpose of this paper is to develop fuzzy TOPSIS method to improve the quality of decision making for species selection. For this propose, the selection of range species was done using Fuzzy-TOPSIS techniques in 2012 in Sarab Sefid rangeland in Boroujerd, Lorestan Province, Iran. In this method, the ratings of various species versus subjective criteria and weights of all criteria were assessed by linguistic variables represented by fuzzy numbers. Fuzzy numbers try to resolve the ambiguity of concepts that are associated with man judgments. A set of pre-defined linguistic variables parameterized by triangular fuzzy numbers was used by the group to evaluate the weights of various criteria and the ratings of each species. To determine the order of species, the closeness coefficient was defined by calculating the distances to Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS). Finally, for the application and verification, an empirical study was performed to demonstrate the model and identify the suitable species. Results show that Fuzzy-TOPSIS method is useful for species selection decision making and the proposed system can provide accurate results. Based on this method, Bromus tomentellus was the best species from frequency viewpoint for the range management.
Alavi, I., Akbari, A., Alinejad-Rokny, H., 2012. Plant type selection for Sarcheshmeh copper mine by fuzzy TOPSIS method. An International Jour. Advanced Engineering Technology and Application, 1(1): 8-13.(In Persian).
Alavi, I. and Alinejad-Rokny,H., 2011. Comparison of fuzzy TOPSIS method for plant species selection (Case Study: Reclamation Plan of Sungun Copper Mine, Iran). Australian Jour. Basic and Applied Sciences, 5(12): 1104-1113. (In Persian).
Ariapour, A., Hadidi, M, Karami, K. and Amiri. F., 2013. Water resources suitability model by using GIS (Case Study: Boroujerd Rangeland, Sarab Sefid). Jour. Rangeland Science, 3(2): 177-188. (In Persian).
Ataei, M., Karamoozian, M., Kakaei, R. Safari, M., 2012. Using fuzzy TOPSIS method for mineral processing plant site selection. Arabian Jour. Geosciences, 10(1): 125-135. (In Persian).
Abo-Sinna, M. A., Amer, A. H. and Ibrahim, A. S., 2008. Extensions of TOPSIS for large scale multi-objective non-linear programming problems with block angular structure. Appl. Math. Model, 32: 292-302.
Ashtiani, B., Haghighirad, F. Makui A. and Montazer, G. A., 2008. Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Applied Soft Computing, 9(2): 457-461. (In Persian).
Caterino, N., Lervolino, I., Manfredi, G. and Cosenza, E., 2008. A comparative analysis of decision making methods for the seismic retrofit of RC buildings. The 14 th World Conference on Earthquake Engineering October 12-17, 2008, Beijing, China.
Chamodrakas, I., Alexopoulou, N. and Martakos, D., 2009. Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS. Expert Syst. Appl., 36: 7409-7415.
Chen, S. J. and Hwang, C. L., 1992. Fuzzy multi attribute decision making, lecture notes in economics and mathematical system series, vol. 375. Springer-Verlag New York.
Chen, C. T., Lin, C. T. and Hwang, S. F., 2006. A fuzzy approach for supplier evaluation and selection in supply chain management. International Jour. Production Economics, 102(2): 289-301.
Chen, T. C. and Tsao, C. Y., 2008. The interval-valued fuzzy TOPSIS method and experimental analysis. Fuzzy Sets Syst. 159(11): 1410-1428.
Chen, S. M. and Lee, L. W., 2010. Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Systems with Applications, 37(4): 2790-2798.
Chu, M. T, Shyu, J, Tzeng, G. H. and Khosla, R., 2007. Comparison among three analytical methods for knowledge communities group-decision analysis. Jour. Expert systems with Applications, 33: 1011-1024.
Chu, T. C. Lin, Y. C., 2009. An interval arithmetic based fuzzy TOPSIS model. Expert Syst. Appl., 36: 10870-10876.
Deng, H., Yeh, C. H. and Willis, R. J., 2000. Inter-company comparison using modified TOPSIS with objective weights. Comput. Oper. Res., 27: 963-973.
Ertugrul, I. and Karakasoglu, N., 2006. Fuzzy TOPSIS method for academic member selection in engineering faculty. International joint conferences on computer, information and systems sciences and engineering (CIS2EO6) December 4-14.
Hashemi, M., and Amiri, M., 2013. Temporal dimension evaluation by fuzzy TOPSIS method. International Jour. Architecture and Urban Development, 3(2):1-6. (In Persian).
Hwang, C. and Yoon, K., 1981. Multiple attribute decision making methods and application, Springer, New York. USA.
Jahanshahloo, G. R., Hosseinzadeh Lotfi, F. and Izadikhah, M., 2006. Extension of the TOPSIS method for decision-making problems with fuzzy data. Applied Mathematics and Computation, 181(2): 1544–1551. (In Persian).
Kahraman, C., Engin, O., Kabak, Ö. and Kaya, Ï., 2009. Information systems outsourcing decisions using a group decision-making approach. Eng. Appl. Artif. Intell., 22: 832-841.
Karsak, E. E., 2002. Distance-based fuzzy MCDM approach for evaluating flexible manufacturing system alternatives. International Jour. Production Research, 40(13): 3167–3181.
Kaufman, A. and Gupta, M. M., 1988. Introduction of fuzzy arithmetic: Theory and applications, Van Nostrand, New York.
Li, D. F., 2007. Compromise ratio method for fuzzy multi-attribute group decision making. Appl. Soft. Comput., 7(3): 807-817.
Liang, G. S., 1999. Fuzzy MCDM based on ideal and anti-ideal concepts. European Jour. Operational Research, 112(3): 682-691.
Lin, H. T. and Chang, W. L., 2008. Order selection and pricing methods using flexible quantity and fuzzy approach for buyer evaluation. Eur. Jour. Oper. Res., 187: 415-428.
Mashayekhan, A. and Mahiny, S., 2011. A multi-criteria evaluation approach to delineation of suitable area for planting trees. Jour. Rangeland Science, 1(3): 225-234. (In Persian).
Shih, H. S., Shyur, H. J. and Lee, E. S., 2007. An extension of TOPSIS for group decision making, Math. Comput. Model, 45: 801-813.
Sun, C. C. and Lin, G. T. R., 2009. Using fuzzy TOPSIS method for evaluating the competitive advantages of shopping websites. Expert Syst. Appl., 36: 11764-11771.
Triantaphyllou, E. and Lin, C. L., 1996. Development and evaluation of five fuzzy multi attribute decision making methods. International Jour. Approximate Reasoning, 14(4): 281–310.
Wang, T. C and Chang, T. H., 2007. Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Syst. App., 33: 870-880.
Wang Y. J. and Lee, H. S., 2007. “Generalizing TOPSIS for fuzzy multiple- criteria group decision-making,” Computers and Mathematics with Applications, 53(11): 1762-1772.
Yang, T. and Hung, C. C., 2007. Multiple-attribute decision making methods for plant layout design problem. Robotics and Computer-Integrated Manufacturing, 23: 126–137.
Yong, D., 2006. Plant location selection based on fuzzy TOPSIS. Int. Jour. Adv. Manuf. Technol, 28: 839-844.
Zadeh, L. A., 1965. Fuzzy sets. Information and Control, 8: 338–353.
Zadeh, L. A., 1975. The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 8: 199–249(I). 301–357 (II).
Zanakis, S., Solomon, H. A., Wishart, N. and Dublish, S., 1998. Multi-attribute decision making: A simulation comparison of select methods. Eur. Jour. Oper. Res., 107: 507-529.