Materials selection criteria weighting method using analytic hierarchy process (AHP) with simplest questionnaire and modifying method of inconsistent pairwise comparison matrix

Author(s):  
Won-Chol Yang ◽  
Jae-Bok Ri ◽  
Ji-Yon Yang ◽  
Ju-Song Kim

The analytic hierarchy process has been widely used to determine subjective weights of materials selection criteria in materials selection using multi-criteria decision-making. However, the analytic hierarchy process has some drawbacks: it is difficult to construct a pairwise comparison matrix and meet the consistency requirement. First, we propose a new simplest questionnaire to perform the pairwise comparison without confusion, conventionally and easily. Next, we propose an improved modifying method for inconsistent pairwise comparison matrix according to the following principles: (1) the elements of the reconstructed pairwise comparison matrix should be nine-point scales, (2) the number and modifying the amount of the modified elements should be as small as possible and (3) the deviation between the original and reconstructed pairwise comparison matrixes should be as small as possible. The outline of the proposed modifying method is as follows: (1) calculate the consistency ration decrements of all the pairwise comparison matrixes reconstructed by modifying every element of the original pairwise comparison matrix to the lower and upper adjacent nine-point scales and (2) find the element with the maximum consistency ratio decrement and modify it to the lower or upper adjacent scale. To illustrate the effectiveness, we apply the proposed methods to determine the criteria weights for selecting the best phase change material used in a solar domestic hot water system, and apply the proposed modifying method to some examples from the published papers, and compare the performances with some previous methods. The simplest questionnaire and improved modifying method help materials designers and engineers to apply the analytic hierarchy process method in materials design and optimization problems, much more actively.

Author(s):  
Izak Johannes Roux ◽  
Dr. Christos Makrigeorgis

<p>In 2013, oil companies in Alberta, Canada invested $32 billion in new oil-sands projects.  Despite the size of this investment, there is a demonstrable deficiency in the uniformity and understanding of environmental legislation requirements that translate into increased project compliance risks. In this paper, we applied the Analytic Hierarchy Process (AHP) to develop a priority list of environmental regulatory compliance risk criteria for oil-sands projects.  AHP belongs to the family of multicriteria decision-making (MCDM) techniques that utilizes a pairwise comparison matrix solicited from subject matter experts (SMEs) in the field as input.  The overall methodology itself consisted of 4 phases: (1) identification of the initial list of N potential environmental compliance risk criteria and verification of these criteria via a pilot survey; (2) formation of a pairwise comparison survey in the form of an N(N-1)/2 comparison matrix based on the verified criteria; (3) administration of the pairwise comparison matrix to a sample of 16 industry-specific SME’s; and (4) the application of the AHP method using SuperDecisions as a tool on the collected sample to rank the identified risk criteria. Our demonstrated results can potentially inform Alberta oil sands industry leaders about the ranking and utility of specific compliance risks as understood by experts and enable a more focused environmental compliance action to help increase legislative and public trust.</p>


2011 ◽  
Vol 99-100 ◽  
pp. 852-856
Author(s):  
You Zhu Li ◽  
De Hua He

In the study, electronic market credit risk evaluation for agricultural products based on analytic hierarchy process is proposed.Firstly, the evaluation indexes are analyzed and the hierarchic tree is formulated based on the evaluation indexes.Then, pairwise comparison matrix is established,and the consistency of discriminant matrix is judged.When the consistency of discriminant matrix is satisfied,the weight vector of the indexes which are used to establish the pairwise comparison matrix are obtained. And weight of each index is obtained.Finally,final decision making is obtained. The experimental results show that the evaluation of electronic market credit risk evaluation for agricultural products based on analytic hierarchy process is effective.


Author(s):  
Gokulananda Patel ◽  
Godwin D Mjema ◽  
Kasio M Godwin

The Analytic Hierarchy Process (AHP) provides a way to rank the alternatives by deriving priorities. In this paper we used Linear Programming (LP) models to estimate the weights of a pairwise comparison matrix derived within the frame work of the Analytic Hierarchy Process. The priorities obtained for the alternatives served as the coefficients of the objective function of linear programming to optimize a human resource problem at Bakhresa Food Product Limited (BFPL).


2012 ◽  
Vol 433-440 ◽  
pp. 2109-2113
Author(s):  
Xiao Zhang

Evaluation of enterprise marketing performance has a great importance for enterprise to formulate marketing strategy and carry out marketing activity.Evaluation for enterprise marketing performance based on analytic hierarchy process is proposed in the paper.Analytic hierarchy process is used to perform multi-criteria decision analysis in order to determine the relative importance in the decision matrix.The pairwise comparison matrix by using the pairwise comparison of the indexes in same layer is established.Local weight and global weight are computated by using the pairwise comparison matrix. Marketing condition of a certain enterprise is applied to evaluate for enterprise marketing performance. It can be seen that enterprise marketing performance based on analytic hierarchy process is effective.


2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Shunsuke Shiraishi ◽  
Tsuneshi Obata

AbstractNowadays, the analytic hierarchy process is an established method of multiple criteria decision making in the field of Operations Research. Pairwise comparison matrix plays a crucial role in the analytic hierarchy process. The principal (maximum magnitude) eigenvalue of the pairwise comparison matrix can be utilized for measuring the consistency of the decision maker’s judgment. The simple transformation of the maximum magnitude eigenvalue is known to be Saaty’s consistency index. In this short note, we shed light on the characteristic polynomial of a pairwise comparison matrix of third order. We will show that the only real-number root of the characteristic equation is the maximum magnitude eigenvalue of the third-order pairwise comparison matrix. The unique real-number root appears in the area where it is greater than 3, which is equal to the order of the matrix. By applying usual Newton’s method to the characteristic polynomial of the third-order pairwise comparison matrix, we see that the sequence generated from the initial value of 3 always converges to the maximum magnitude eigenvalue.


Author(s):  
LONG-TING WU ◽  
XIA CUI ◽  
RU-WEI DAI

The Analytic Hierarchy Process (AHP) uses pairwise comparison to evaluate alternatives' advantages to a certain criterion. For decision-making problem with many different criteria and alternatives, pairwise comparison causes a prolonged decision-making period and rises fatigue in decision-makers' mentality. A question of practical value is if there exists a way to reduce judgment number and what influence the reduction will have on the overall evaluation of alternative ratings. To answer this question, we introduce scale error and judgment error into AHP judgment matrix. By expanding the scales defined in the AHP, scale error is eliminated. Taking judgment error as random variable, a new estimator to calculate priority vector is presented. In the end, an example is proved to show lowering judgment number will increase the probability of larger errors appearing in priority vector computation.


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