An Improved Method for Solving Multi-Attribute Problem in Transportation Mode Decision Making Process

2014 ◽  
Vol 1030-1032 ◽  
pp. 1961-1965
Author(s):  
Bao Shan Lin ◽  
Yan Bin Fan
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Entropy Method ◽  
Topsis Method ◽  
Transportation Mode ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
Time Price ◽  
Transportation Activity

In logistics activities, the choice of the transportation mode involves time, price, safety, and many other factors, it is a typical multi-attribute decision making problem. Traditionally, we usually adopt a certain decision-making method to solve such problems, but the resulting solution is often difficult to achieve our desired results. This article tries to combine AHP, information entropy method and the TOPSIS method to solve the multiple-attribute decision making problems in the process of transportation activity, and finally a case is given.

scholarly journals Possibility Neutrosophic Cubic Sets and Their Application to Multiple Attribute Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 269 ◽  
Author(s):  
Huiling Xue ◽  
Xiaotong Yang ◽  
Chunfang Chen
Keyword(s):  
Decision Making ◽  
Binary Operation ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Membership Degree ◽  
Neutrosophic Sets ◽  
Important Indicator ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making

The neutrosophic cubic sets are an extension of the cubic sets to the neutrosophic sets. It contains three variables, which respectively represent the membership degree, non-membership degree and uncertainty of the element to the set. The score function is an important indicator in the multi-attribute decision-making problem. In this paper, we consider the possibility that an element belongs to a set and put forward the concept of possibility neutrosophic cubic sets. On this basis, we introduce some related concepts and give the binary operation of possibility neutrosophic cubic sets and use specific examples to supplement the corresponding definition. Meanwhile, a decision-making method based on the score function of possibility neutrosophic cubic sets is proposed and a numerical example is given to illustrate the effectiveness of the proposed method.

Entropy method of determining the attribute weights of interval numbers based on relative superiority

2021 ◽  
pp. 1-8
Author(s):  
Lin Li ◽  
Tiejun Ci ◽  
Xiaoyu Yang ◽  
Heng Du ◽  
Haocan Ma ◽  
...  
Keyword(s):  
Decision Making ◽  
Basic Principle ◽  
Multiple Attribute Decision Making ◽  
Entropy Method ◽  
Interval Numbers ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Train Of Thought

In view of the multi-attribute decision making problems which the attribute values are in the forms of interval numbers, the paper presents an entropy method to obtain the attribute weights using the relative superiority concept. Firstly, the concept of this kind of problem is explained; Then in the light of the basic principle of the traditional entropy value method and train of thought, it given the calculation steps of weights using the relative superiority about the attribute value is interval number multiple attribute decision making problems. Its core is that relative superiority judgment matrix is obtained by comparing with two sets of interval numbers under the same indicator, which the group of interval numbers is equivalently mapped to the exact value form with the merits of relationship, then the weights of each indicator are calculated. Finally, the method is illustrated by giving an example.

scholarly journals DEVELOPMENT OF DECISION SUPPORT SYSTEM DETERMINING THE STUDENT AS SCHOLARSHIP RECIPIENTS BY FUZZY MULTI ATTRIBUTE DECISION MAKING (FMADM)

2014 ◽  
Vol 9 (2) ◽  
pp. 75 ◽  
Author(s):  
Hoga Saragih ◽  
Murni Marbun ◽  
Bobby Reza
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Attribute Decision Making ◽  
Topsis Method ◽  
Software Application ◽  
Multiple Attribute ◽  
Scholarship Recipients ◽  
Multi Attribute Decision Making

This research is the design of a decision support system (DSS) to determining the student as scholarship recipients of the STMIK Pelita Nusantara, Medan, Indonesia, with the approach of Fuzzy Multi Attribute Decision Making (FMADM) with TOPSIS method. Approach to Fuzzy Multiple Attribute Decision Making (FMADM) by specifying the values of the weights for each of the criteria or attributes and TOPSIS method for selecting student scholarship recipients. Implementation of a decision support system that can show the interaction of the user with the software application built using Visual Basic 2008 programming language. Conclusion the results obtained from the discussion shows that the approach with FMADM TOPSIS give final value calculation results ordered that can help decision makers determine the student deserves the scholarship. The existence of a decision support system that has been designed so the process of determining a student scholarship recipients more accurately, quickly, and accurately.

TOPSIS Method for Multiple Attribute Decision Making Problem in Intuitionistic Fuzzy Setting

2013 ◽  
Vol 427-429 ◽  
pp. 1888-1891
Author(s):  
Yuan Yuan He ◽  
Zai Wu Gong
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Topsis Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Fuzzy Setting

This paper is concerned with a TOPSIS method for fuzzy multiple attribute decision making, in which the information about attribute weights is completely known and the attribute values take form of intuitionistic fuzzy numbers. A class of distance for describing the deviation degrees between intuitionistic fuzzy sets is used to measure difference between two alternatives. A model of TOPSIS is designed with the introduction of the particular closeness coefficient composed of similarity degrees. Then, we apply the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their closeness coefficients. Finally, a numerical example is given to show the feasibility and effectiveness of the method.

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