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LI Mei, WU Chong, ZHANG Lei. Intuitionistic Fuzzy Decision Making Method based on Prospect Theory and Its Application in Distribution Center Location[J]. Journal of Xihua University(Natural Science Edition), 2015, 34(6): 1-5, 11. DOI: 10.3969/j.issn.1673-159X.2015.06.001
Citation: LI Mei, WU Chong, ZHANG Lei. Intuitionistic Fuzzy Decision Making Method based on Prospect Theory and Its Application in Distribution Center Location[J]. Journal of Xihua University(Natural Science Edition), 2015, 34(6): 1-5, 11. DOI: 10.3969/j.issn.1673-159X.2015.06.001

Intuitionistic Fuzzy Decision Making Method based on Prospect Theory and Its Application in Distribution Center Location

  • In this paper, we construct an intuitionistic fuzzy multiple attribute decision making method based on prospect theory in order to improve the location efficiency of the distribution center, and apply it to the location decision of distribution center.Firstly, this paper introduces the related concepts of intuitionistic fuzzy sets; secondly, proposes an improved scoring function algorithm and builds a new decision-making model with the prospect theory, based on which the decision process of the distribution center selection is planned, and then the evaluation indicator system is built selecting the operating cost, the traffic factor and the customer service as the evaluation indicators; finally, the decision about the distribution center location of some electric business platform is evaluated by a numerical example.This method on the one hand introduces the intuitionistic fuzzy number in the decision evaluation, and takes into account the uncertainty of expert evaluation and the degree of uncertainty.On the other hand, making a comprehensive evaluation with the method of decision-making based on prospect theory, has fully considered the difference of the risk preference in the face of the income and the loss, so that the decision result is more consistent with people's true intention and we can get more reasonable decision effect from it.The calculation result shows the results of this paper are consistent with the results of the original intuitionistic fuzzy TOPSIS decision method, and the former is more differentiated, thus more advantageous to the distribution of the center level, and then we can finally improve the quality of decision-making and reduce the risk of decision-making.
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