| The real estate investment decision-making process often has very limited statistical data, with human activity, there is a large fluctuation in the data, and the data's distribution is not regular. How to establish an effective decision-making method is particularly important.This paper is based on the volatility of statistical data, no regular distribution in the data, and factors have not determined the relationship between the number of cases, then uses the combination of the TOPSIS optimization and GREY relevancy about decision-making on investment in real estate projects for research. Firstly, this paper does a synthetic summery of the real estate investment projects and analyzes the system. Secondly it brings up the detailed evaluation methods and decision-making methods about the real estate projects, including static analysis, dynamic analysis, break-even analysis, the sensitivity analysis and probability analysis. Because TOPSIS optimization is based on the samples of raw data, only analyzes the distance between data analysis, the data sequence does not reflect the situation changes, but the GREY relevancy can make up for this precisely. So in the last part of this paper, it will combine the two kinds of methods, bring up a new method to the real estate projects for integrated decision-making.Through empirical research, the paper verifies that the methods of combination of the TOPSIS optimization and GREY relevancy is reasonable and scientific. At the same time, the paper carries out some reasonable suggestion of the real estate investment decision-making. |
PDF Full Text Request