Method of Weight Assignment for Multi-Criterion Based on Grey Interval AHP

2011 ◽  
Vol 243-249 ◽  
pp. 5285-5288 ◽  
Author(s):  
Chun Yan Xia ◽  
Yan Jie Liu ◽  
Dong Mei Liu
Keyword(s):  
Uncertain Information ◽  
Analytic Hierarchy ◽  
Interval Numbers ◽  
Weight Assignment ◽  
Relational Degree ◽  
Interval Relation ◽  
Relation Analysis ◽  
Hierarchy Process ◽  
Grey Relation ◽  
Evaluation Information

According to the problem of weight assignment for multi-criterion in uncertain information system, the disadvantage of the traditional analytic hierarchy process (AHP) is analyzed; the Method of weight assignment for multi-criterion based on grey interval AHP is put forward. At first, grey interval numbers are imported as a mean to deal with the evaluation information in the proposed method, the quantitative representation of uncertain information is carried out; the loss of information is decreased. Then, base on grey relation analysis and AHP, the relational degree of each criterion is calculated by using grey interval relation analysis, which reflects the relative important degree of each criterion. The judgment matrix is constructed, which fits in with consistent requirements spontaneously. The weight value of each criterion is achieved. Finally, the evaluation example proves that the proposed method is feasible.

scholarly journals A New Evaluation Methodology for Quality Goals Extended by D Number Theory and FAHP

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 206
Author(s):  
Hongming Mo
Keyword(s):  
Number Theory ◽  
Process Management ◽  
Evidence Theory ◽  
Evaluation Methodology ◽  
Uncertain Information ◽  
Mathematical Tool ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Hierarchy Process ◽  
Evaluation Information

Evaluation of quality goals is an important issue in process management, which essentially is a multi-attribute decision-making (MADM) problem. The process of assessment inevitably involves uncertain information. The two crucial points in an MADM problem are to obtain weight of attributes and to handle uncertain information. D number theory is a new mathematical tool to deal with uncertain information, which is an extension of evidence theory. The fuzzy analytic hierarchy process (FAHP) provides a hierarchical way to model MADM problems, and the comparison analysis among attributes is applied to obtain the weight of attributes. FAHP uses a triangle fuzzy number rather than a crisp number to represent the evaluation information, which fully considers the hesitation to give a evaluation. Inspired by the features of D number theory and FAHP, a D-FAHP method is proposed to evaluate quality goals in this paper. Within the proposed method, FAHP is used to obtain the weight of each attribute, and the integration property of D number theory is carried out to fuse information. A numerical example is presented to demonstrate the effectiveness of the proposed method. Some necessary discussions are provided to illustrate the advantages of the proposed method.

Probabilistic Linguistic Analytic Hierarchy Process and Its Application on the Performance Assessment of Xiongan New Area

2018 ◽  
Vol 17 (06) ◽  
pp. 1693-1724 ◽  
Author(s):  
Wanying Xie ◽  
Zeshui Xu ◽  
Zhiliang Ren ◽  
Hai Wang
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Uncertain Information ◽  
Decision Matrix ◽  
Analytic Hierarchy ◽  
Decision Tools ◽  
Probabilistic Linguistic Term Set ◽  
Complex Decision Making ◽  
The Individual ◽  
Hierarchy Process

Analytic Hierarchy Process (AHP) is one of the most favorable decision tools for dealing with complex decision-making problems. Probabilistic linguistic term set (PLTS) is an up-to-date tool to deal with uncertain information in the decision-making process. In this paper, we extend the AHP to the probabilistic linguistic environment for perfecting the modeling ability of AHP in various decision-making problems. In order to apply the PLTSs to the AHP properly, we first redefine the probabilistic linguistic comparison matrix (PLCM) and propose a new consistency index. Then, we propose a new approach to check and improve the consistency of the PLCMs. After that, we aggregate the individual PLCMs into the collective PLCM and derive the priorities of the collective PLCM. Finally, we combine the priorities with the decision matrix to complete the ranking of alternatives, and a case concerning the performance assessments of three new areas is given and the comparative analysis about the results is performed to demonstrate the feasibility of the proposed method.

Dynamic Positioning System: Systematic Weight Assignment for DP Sub-Systems Using Multi-Criteria Evaluation Technique Analytic Hierarchy Process and Validation Using DP-RI Tool With Deep Learning Algorithm

2019 ◽  
Author(s):  
Charles Fernandez ◽  
Arun Kr. Dev ◽  
Rose Norman ◽  
Wai Lok Woo ◽  
Shashi Bhushan Kumar
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Learning Algorithm ◽  
Real Life ◽  
Operating Conditions ◽  
Dynamic Positioning ◽  
Analytic Hierarchy ◽  
Dynamic Positioning System ◽  
Weight Assignment ◽  
Hierarchy Process

Abstract The Dynamic Positioning (DP) System of a vessel involves complex interactions between a large number of sub-systems. Each sub-system plays a unique role in the continuous overall DP function for safe and reliable operation of the vessel. Rating the significance or assigning weightings to the DP sub-systems in different operating conditions is a complex task that requires input from many stakeholders. The weighting assignment is a critical step in determining the reliability of the DP system during complex marine and offshore operations. Thus, an accurate weighting assignment is crucial as it, in turn, influences the decision-making of the operator concerning the DP system functionality execution. Often DP operators prefer to rely on intuition in assigning the weightings. However, it introduces an inherent uncertainty and level of inconsistency in the decision making. The systematic assignment of weightings requires a clear definition of criteria and objectives and data collection with the DP system operating continuously in different environmental conditions. The sub-systems of the overall DP system are characterized by multi-attributes resulting in a high number of comparisons thereby making weighting distribution complicated. If the weighting distribution was performed by simplifying the attributes, making the decision by excluding part of them or compromising the cognitive efforts, then this could lead to inaccurate decision making. Multi-Criteria Decision Making (MCDM) methods have evolved over several decades and have been used in various applications within the Maritime and Oil and Gas industries. DP, being a complex system, naturally lends itself to the implementation of MCDM techniques to assign weight distribution among its sub-systems. In this paper, the Analytic Hierarchy Process (AHP) methodology is used for weight assignment among the DP sub-systems. An AHP model is effective in obtaining the domain knowledge from numerous experts and representing knowledge-guided indexing. The approach involved examination of several criteria in terms of both quantitative and qualitative variables. A state-of-the-art advisory decision-making tool, Dynamic Positioning Reliability Index (DP-RI), is used to validate the results from AHP. The weighting assignments from AHP are close to the reality and verified using the tool through real-life scenarios.

Application of Extenics Theory to Accuracy Evaluation of Machining Center

2013 ◽  
Vol 397-400 ◽  
pp. 135-139
Author(s):  
Chen Liu ◽  
Xiang Li Bu
Keyword(s):  
Set Theory ◽  
Element Model ◽  
Accuracy Evaluation ◽  
Practical Application ◽  
Analytic Hierarchy ◽  
Evaluation Indexes ◽  
Machining Center ◽  
Relational Degree ◽  
Matter Element Model ◽  
Hierarchy Process

The matter-element model for the accuracy evaluation of the machining center is established based on extenics theory, the accuracy evaluation indexes of machining cente are made of multiple elements. The relational degree is calculated by introducing the relational function in the extension set theory, and the weights of evaluation indexes are defined with AHP (the analytic hierarchy process), so the awaiting evaluation machining center is determined though the accuracy grade. A type of machining center as an example is studied the practical application of the proposed method, the result is reasonable and shows that the method possesses a certain practicability.

scholarly journals An Evidential Fractal Analytic Hierarchy Process Target Recognition Method

2018 ◽  
Vol 68 (4) ◽  
pp. 367 ◽  
Author(s):  
Yuzhen Han ◽  
Yong Deng
Keyword(s):  
Analytic Hierarchy Process ◽  
Target Recognition ◽  
Fractal Theory ◽  
Evidence Theory ◽  
Belief Function ◽  
Uncertain Information ◽  
Fusion Algorithm ◽  
Analytic Hierarchy ◽  
Sensory Data ◽  
Hierarchy Process

<p>Target recognition in uncertain environments is a hot issue, especially in extremely uncertain situation where both the target attribution and the sensor report are not clearly represented. To address this issue, a model which combines fractal theory, Dempster-Shafer evidence theory and analytic hierarchy process (AHP) to classify objects with incomplete information is proposed. The basic probability assignment (BPA), or belief function, can be modelled by conductivity function. The weight of each BPA is determined by AHP. Finally, the collected data are discounted with the weights. The feasibility and validness of proposed model is verified by an evidential classifier case in which sensory data are incomplete and collected from multiple level of granularity. The proposed fusion algorithm takes the advantage of not only efficient modelling of uncertain information, but also efficient combination of uncertain information.</p>

Predicting the End Temperature of Molten Steel Using CBR

2012 ◽  
Vol 164 ◽  
pp. 7-11 ◽  
Author(s):  
De Hua Liu ◽  
Hong Bing Wang ◽  
An Jun Xu
Keyword(s):  
Molten Steel ◽  
Relative Weight ◽  
Case Based Reasoning ◽  
Analytic Hierarchy ◽  
Steel Material ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational ◽  
Hierarchy Process

Steel is a kind of important material. The accurate control about the end temperature of molten steel has significant impact on the quality of steel material. Case Based Reasoning (CBR) is used to predict the end temperature of molten steel in Argon Oxygen Decarburization (AOD). Grey Relational Degree (GRD) with different weights of attributes is adopted to calculate the similarity between cases. Analytic Hierarchy Process (AHP) is taken to determine the weights of attributes. Multiple Linear Regression (MLR) is applied to compute the relative weight of two different attributes for AHP. Two methods, CBR using AHP with Equal Weights (CBR_AHP_EW) and CBR using AHP with Different Weights (CBR_AHP_DW), are employed to for a comparison. The results show that CBR_AHP_DW is effective in predicting the end temperature of molten steel in AOD and CBR_AHP_DW outperforms CBR_AHP_EW.

Quality Evaluation of Belt Conveyor Based on Extenics Theory

2013 ◽  
Vol 694-697 ◽  
pp. 2960-2963 ◽  
Author(s):  
Chen Liu ◽  
Xu Ming Wang
Keyword(s):  
Quality Evaluation ◽  
Element Model ◽  
Belt Conveyor ◽  
Analytic Hierarchy ◽  
Evaluation Indexes ◽  
Quality Grade ◽  
Relational Degree ◽  
Matter Element Model ◽  
Hierarchy Process

Extenics theory is used to establish the matter-element model for the quality evaluation of the belt conveyor. Introducing the relational function in the extension set theory to calculate the relational degree, defining the weights of evaluation indexes with AHP (the analytic hierarchy process), and so the quality grade of the awaiting evaluation belt conveyor can be obtained. Taking a type of belt conveyor as an example to study the practical application of the proposed method, the results show that the method possesses a certain practicability. The method can give a reasonable evaluation on the quality of belt conveyor.

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