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Selecting the Best Installation Location using the Fuzzy Multi-Criteria Decision Making

Journal Name:

  • International Journal of Science and Engineering Investigations

Publication Year:

  • 2013

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
The location problem of an enterprise is very important strategically and plays a significant role in reducing corporate costs and making profits. In this paper, it has been tried to employ a model considering the criteria and sub- criteria to select the best choice among the alternatives suggested for installing the factory. Due to the subjective nature of qualitative criteria and selective nature of the problem, multi-criteria decision model-multiplayer model is selected among different methods. To regard this aspect, an appropriate model combining multiple models is designed and to have more realistic results fuzzy techniques are used. This model tries to select the location with the highest value among all other alternatives by considering all effective factors. The proposed model is designed based on fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution).At first, fuzzy AHP method is used to determine the weights of criteria and sub- criteria. Next, by using the fuzzy TOPSIS method the suggested alternatives are sorted based on the obtained weights.
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REFERENCES

References: 

[1] EFRON.B & TIBSHIRANI.R.J , "AN INTRODUCTION TO THE BOOTSTRAP", MONOGRAPHS ON STATISTICS AND APPLIED PROBABILITY 57, 1979.
[2] Graham M.A., Chakraborti S., Human S.W., "A nonparametric exponentially weighted moving average signed-rank chart for monitoring location". Computational Statistics and Data Analysis 55 (8), 2490–2503, 2011.
[3] Graham.M.A, Mukherjee.A, Chakraborti.S, "Distribution-free exponentially weighted moving average control charts for monitoring unknown location", Computational Statistics and Data Analysis, 2012.
[4] Lucas J. M., Saccucci M. S., "Exponentially weighted moving average control schemes: Properties and enhancements". Technometrics, 32, 1–12, 1990.
[5] Chang D.Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655.
[6] C.L. Hwang, K. Yoon, Multiple Attributes decision Making Methods and Applications, Springer, Berlin Heidelberg (1981).
[7] Chen, C. T., Lin, C. T., & Huang, S. F. (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102, 289–301.
[8] Ertugrul I., Karakasoglu N. (2007). Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Systems with Applications, 36(1), 702–715.
[9] R.E. Bellman, L.A. Zadeh, Decision-making in a fuzzy environment, Management Sci.17 (4) (1970) 141-164.
[10] T.L. Saaty, The Analytic Hierarchy Process, McGraw- Hill, New York, 1980.

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