Advances in Pure Mathematics
Vol.06 No.12(2016), Article ID:71842,11 pages
10.4236/apm.2016.612062
A Multi-Attribute Decision Making for Investment Decision Based on D Numbers Methods
Qian Zuo, Xuanhua Qin, Youzhen Tian, Daijun Wei
School of Science, Hubei University for Nationalities, Enshi, China

Copyright © 2016 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).
http://creativecommons.org/licenses/by/4.0/



Received: October 7, 2016; Accepted: November 5, 2016; Published: November 8, 2016
ABSTRACT
Investment decision is a traditional multi-attribute decision making (MADM) problem since it has many uncertainty factors and incomplete information such as investment value, cost, sales, etc. D numbers theory is a useful tool to deal with uncertainty factors and incomplete information. In this paper, interval number and D numbers theory are revealed in the uncertain factor and incomplete information of investment decision. The weights of uncertain factors are calculated using entropy weight method. Thus, a new MADM model for investment decision based on D numbers theory is proposed. Numerical example is used to illustrate the efficiency of the proposed method.
Keywords:
Uncertainty, MADM, Investment Decision, D Numbers, Entropy Weight

1. Introduction
The aim of investment decision is to make maximize gains and minimize risk under uncertain environment. Variance portfolio model was a powerful tool to handle investment decision and established by Markowitzin in 1952 [1] [2] , which marked the beginning of the model securities portfolio investment theory. This model, Markowitz’s Portfolio theory [3] [4] [5] [6] , was modified by Sharpes Capital Asset Pricing model [7] [8] and Rosss Arbitrage Pricing theory [9] [10] [11] , then it was used to solve the investment decision making problem. In these methods, the factor of investment decision is usually represented by real numbers. However, indeed, the investment decision making is relative to many criteria, which are uncertainty. Investment decision making can be seen as a MADM problem. MADM has been studied by many researchers [12] [13] [14] [15] [16] . For MADM, two problems are key issues. One is that how to represent uncertain factors and another is how to fuse these uncertain factors. Many methods are applied to reveal uncertainty factors such as fuzzy set method [17] , rough set method [18] , probability method [19] [20] and interval numbers [21] [22] . The interval number is an effective way to solve the problem of uncertainty since its value range is bigger than real number, and that has simple forms. Thus, the interval numbers represented kinds of uncertain factors for investment decision making [23] [24] . For the second problem, Dempster-Shafer (D-S) theory was a useful tool to handle it. D-S theory was first proposed by Dempster in 1967, which was further developed by Shafer in 1976. The basic probability assignment (BPA) in Dempster-Shafer (D-S) theory represents the information of both certain or uncertain. Furthermore, the Depmster’s combination rule can combine multiple BPAs. Thus, Dempster-Shafer theory of evidence has been widely used in multiple criteria decision making [25] - [30] . However, D-S theory has some drawback, such as the completeness constraint and exclusiveness hypothesis [31] . As improved D-S theory, D numbers theory is proposed in references [31] [32] . D numbers theory removes some strong hypotheses from Dempster-Shafer theory of evidence. It enables the D numbers theory more powerful in dealing with uncertainty as well as incompleteness. In D numbers theory, the elements may be compatible. Meanwhile, framework may be incomplete. D numbers theory is a powerful tool to handle incomplete and uncertainty information. Thus, D numbers theory is applied into many fields, such as environmental impact assessment [33] [34] , bridge condition assessment [35] and curtain grouting efficiency assessment [36] . Our goal is to handle investment decision problem using D numbers method. In this paper, the uncertain information of investment decision is revealed using interval number and D numbers theory. Meanwhile, the weights of uncertain factors are calculated using entropy weight method. Thus, a new MADM model for investment decision is proposed. The paper is organized as follows. The preliminaries of interval number, D numbers theory and entropy weight method are introduced in Section 2. The proposed method and an illustrative example are given in Section 3. Some conclusions are drawn in Section 4.
2. Preliminaries
2.1. Interval Number Method
Interval number is actual a collection of all real numbers on a closed interval. Interval number represents a kind of uncertainty, and it has a great potential for application in different fields, such as establish fuzzy portfolio model and multi-objective portfolio model [37] [38] . An interval number is denoted as
, which is defined as follows [37] .
Definition 2.1. If
is the upper bound of the range,
is the lower range, we have:
(1)
Especially, the interval number
is a real number when
.
For two interval numbers,
and
, they are some properties as follows,
1)
if
and
.
2)
.
3)
, and when
,
.
The interval decision matrix is key factors for investment decision. The interval decision is defined as below.
Definition 2.2. A decision matrix
is composed of interval number
, where
(2)
In investment decision, the attributes can be divided into two types: benefit type and cost type. For example, profit is benefit type, while risk is cost type. To eliminate the influence of different physical dimension for the decision result, the standardized original decision matrix is denoted as


or

where 

2.2. D Numbers Theory
D numbers theory is proposed by Deng [31] , which is the development of Dempster- Shafer theory of evidence. It is brief introduced as follows,
Definition 2.3. Let 


where 

Definition 2.4. For a discrete set






or be represented simply as:
An example is given to describe the D numbers. For MADM, the set of 

where




where




Definition 2.5. For a given D numbers, the overall assessment is defined as:

In Dempster-Shafer theory of evidence, two BPAs can be fused into a BPA. Similarity, in D numbers method, the fusing rules of two D numbers have been proposed [31] . It is defined as below,
Definition 2.6. Let 

The combination of 



with


where:
where 

2.3. Interval Numbers Decision Based on Entropy Weight
According to the basic principle of information theory, information is the orderly degree of a measurement system. The entropy is a measurement of disorder degree in a system. The absolute value of them is equal, while their symbol is inverse. Therefore, many scholars use Entropy weight method to measure the weight. The smaller information entropy is, the higher weight is [8] [9] . Entropy weight method is introduced as below.
Definition 2.7. For MADM, any solution set


Using the formula (2) (3) (4), we have the standardized matrix



Then, attribute 

Specially, we have: 
According to information entropy, the attribute’s weight vector can be calculated as follows,
with

The comprehensive attribute values can be obtained as below,

According to the value of
3. Proposed Method
3.1. A New MADA Based on D Numbers Methods
In this section, a new MADA model for investment project is proposed. In this model, firstly, the uncertain information of investment decision is represented by using interval number and D numbers theory. The uncertain information is given as follows,
where

where 

the uncertainty information. We have: 

tion (2), the decision matrix of uncertainty factors A is obtained. Secondly, using Equation (6), the corresponding matrix is obtained. Considering type of factors, the corresponding matrix must change into the standard matrix R. Thus, the standard matrix R is obtained according to Equations (3), (4) and (11) at third step. Lastly, the weights of uncertainty factors are calculated by using entropy weight method. According to Equation (14), the value of each decision is calculated. So, we make decision according to the value of each decision.
3.2. A Numerical Example
In this section, a numerical example is introduced for describing the proposed method. Supposing for promoting a new product, a company plans to choose a project from the four investment projects. These investment projects are denoted as
















where
For calculating the weight of each attribute, the process can be divided into four steps.
Step 1. Using the formula:
Step 2. We replace the D numbers in the matrix by 

Step 3. The expected net present value and risk profit value are the benefit type. Amount of investment and risk loss value are the cost benefit attributes. Using the
formula (3) (4) (11), we can get the normalized matrix

Step 4. Using the formula (12) obtains the output information entropy of attribute
According to Equation (13), the attribute’s weight vector can be calculated as follows,
Using Equation (14), each value of scheme 
So, we have

4. Conclusion
Although there are many methods to deal with investment decision problems, no method represents the uncertainty and incomplete information in investment project. In this paper, the combination of interval number and D numbers method is used to deal with investment decision problems. All the assessments are represented by the combination of interval number and D numbers. Meanwhile, the weights of uncertainty factors are calculated using entropy weight method. Thus, a new MADM model for investment decision is proposed. A numerical example is used to illustrate the efficiency of the proposed method.
Acknowledgements
The work is partially supported by Found of Educational Commission of Hubei Province of China (Grant No. D20151902), the Doctoral Scientific Research Foundation of Hubei University for Nationalities (Grant No. my2014b003), the Training Programs of Innovation and Entrepreneurship for Undergraduates of Hubei University for Nationalities (Grant No. 2014Z046).
Cite this paper
Zuo, Q., Qin, X.H., Tian, Y.Z. and Wei, D.J. (2016) A Multi-Attribute Decision Making for Investment Decision Based on D Numbers Methods. Advances in Pure Mathematics, 6, 765-775. http://dx.doi.org/10.4236/apm.2016.612062
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