Ranking range models under incomplete attribute weight information in the selected six MADM methods

2021 ◽  
Author(s):  
Yating Liu ◽  
Huali Tang ◽  
Haiming Liang ◽  
Hengjie Zhang ◽  
Cong‐Cong Li ◽  
...  
Keyword(s):  
Attribute Weight

scholarly journals Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 37
Author(s):  
Ye Li ◽  
Yisheng Liu
Keyword(s):  
Decision Making ◽  
Qualitative Evaluation ◽  
Multiple Attribute Decision Making ◽  
Two Dimensional ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weight ◽  
Model Based ◽  
Subjective Weight ◽  
Multiple Attribute

Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

A Novel Discovery Technique on Attribute Weight of Engine CBR Design System

2010 ◽  
Vol 97-101 ◽  
pp. 3714-3717 ◽  
Author(s):  
Wei Yan ◽  
Qi Gao ◽  
Zheng Gang Liu ◽  
Shan Hui Zhang ◽  
Yu Ping Hu
Keyword(s):  
Evolutionary Programming ◽  
Programming Algorithm ◽  
Design System ◽  
Reference Case ◽  
Attribute Weight ◽  
Case Base ◽  
Mutation Strategies ◽  
Group Self ◽  
Gauss Operator ◽  
Self Adaptive

An improved multi-group self-adaptive evolutionary programming Algorithm is used to get adapt attribute weight for CBR system. Firstly, this paper analyses the adaptability function based on reference case base REF and testing case base TEST, develops a novel Bi-group self-adaptive evolutionary programming that overcome the lack of conventional evolutionary programming. In this Novel algorithm, evolution of Cauchy operator and Gauss operator are parallel performed with different mutation strategies, and the Gauss operator owns the ability of self-adaptation according to the variation of adaptability function. Information is exchanged when sub-groups are reorganized. Experiment results prove the validity of self-adaptive Algorithm and CBR design system is used successfully in engine design process.

Research on Material Selection with Multi-Attribute Decision Method and G1 Method

2014 ◽  
Vol 952 ◽  
pp. 20-24 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Topsis Method ◽  
Attribute Weight ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Optimal Material ◽  
Selection Of ◽  
Better Than

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Many factors (attributes) need to be considered in material selection process, and thus material selection problem is a multi-attribute decision making (MADM) problem. This paper proposes a new MADM method for material selection problem. G1 method does not need to test consistency of the judgment matrix. Thus it is better than AHP. In this paper, firstly, we use the G1 method to determine the attribute weight. Then TOPSIS method is used to calculate the closeness of the candidate materials with respect positive solution. A practical material selection case is used to demonstrate the effectiveness and feasibility of the proposed method.

scholarly journals Sistem Pakar pada Sistem Pembayaran Uang Kuliah Cicilan Menggunakan Metode Weighted Product (Studi Kasus Universitas Dharma Andalas)

2021 ◽  
pp. 36-41
Author(s):  
Rahmad Supriadi ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Calculation Method ◽  
Private University ◽  
Tuition Fees ◽  
Accuracy Rate ◽  
Attribute Weight ◽  
Operational Costs ◽  
Weight Value ◽  
Product Method ◽  
The City ◽  
Manual Calculation

Dharma Andalas University is a change in form from the Dharma Andalas Higher School of Economics (STIE). Dharma Andalas University is one of the private universities in the city of Padang which is under the auspices of the Andalas Dharma Education Foundation (YPDA) which is directly fostered by the Andalas University alumni association. Dharma Andalas University is a private university so operational costs come from student tuition fees. Payment of tuition fees is an obligation of every student, considering that tuition fees are quite expensive, Dharma Andalas University provides relief for students to make tuition payments in installments. The purpose of this study is to assist the leadership in making a decision to pay installments using the Weighted Product method. In this study, the data processed is the data of students who apply for installment tuition payments at Dharma Andalas University. The data processing is to determine the criteria for each alternative by multiplying for attribute match reting, then rank with the attribute weight value which results in the vector value V, then the vector value V is ranked from the highest value to the lowest value where the highest value will be prioritized. Furthermore compared to the manual calculation method with a system that has been made, the results are the same with an accuracy rate of 97%, so that it can be recommended to the leadership to help make decisions about the payment of tuition installments.

scholarly journals Uncertain Multiplicative Language Decision Method Based on Group Compromise Framework for Evaluation of Mobile Medical APPs in China

2020 ◽  
Vol 17 (8) ◽  
pp. 2858
Author(s):  
Junchang Li ◽  
Jiantong Zhang ◽  
Ye Ding
Keyword(s):  
Health Management ◽  
Medical Application ◽  
Assessment System ◽  
Medical Apps ◽  
Attribute Weight ◽  
Group Ranking ◽  
Medical App ◽  
Multiple Attribute ◽  
The Individual ◽  
Mobile Medical Apps

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel multiple attribute group decision making algorithm based on group compromise framework, which need not determine the weight of decision-maker. The algorithm utilized an uncertain multiplicative linguistic variable to measure the individual original preference to express the real evaluation information as much as possible. The attribute weight was calculated by maximizing the differences among alternatives. It determined the individual alternatives ranking according to the net flow of each alternative. By solved the 0–1 optimal model with the objective of minimizing the differences between individual ranking, the ultimate group compromise ranking was obtained. Then we took 10 well-known M-medical APPs in Chinese as an example, we summarized service categories provided for users and constructed the assessment system consisting of 8 indexes considering the service quality users are concerned with. Finally, the effectiveness and superiority of the proposed method and the consistency of ranking results were verified, through comparing the group ranking results of 3 similar algorithms. The experiments show that group compromise ranking is sensitive to attribute weight.

Computation Model of Case Similarity Based on Uneven Weight Distance Coefficient

2010 ◽  
Vol 44-47 ◽  
pp. 3965-3969
Author(s):  
Shou Ming Hou ◽  
Li Juan He ◽  
Wen Peng Xu ◽  
Hua Tao Fan ◽  
Zhong Qi Sheng
Keyword(s):  
Conceptual Design ◽  
Rapid Response ◽  
Computational Method ◽  
Structure Model ◽  
Computation Model ◽  
Attribute Weight ◽  
Retrieval Problem ◽  
Similarity Computation ◽  
Rolling Guide ◽  
Distance Coefficient

In order to solve the retrieval problem of design example in rapid response design, similarity computation model among design examples is given, computation of attribute weight of design example is done based on the method of uneven weight distance coefficient, computation of similarity between product structure model that meet the requirement of customers and design examples existed is done by the method of combination weight. This method has been applied in rolling guide conceptual design based on example inference, the result indicated that the weight computational method proposed is simple and the reliability is good, it can solve the intelligent retrieval problem of design examples in rapid response design.

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