scholarly journals A Partial-Consensus Posterior-Aggregation FAHP Method—Supplier Selection Problem as an Example

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 179 ◽  
Author(s):  
Yu-Cheng Wang ◽  
Tin-Chih Chen

Existing fuzzy analytic hierarchy process (FAHP) methods usually aggregate the fuzzy pairwise comparison results produced by multiple decision-makers (DMs) rather than the fuzzy weights estimations. This is problematic because fuzzy pairwise comparison results are subject to uncertainty and lack consensus. To address this problem, a partial-consensus posterior-aggregation FAHP (PCPA-FAHP) approach is proposed in this study. The PCPA-FAHP approach seeks a partial consensus among most DMs instead of an overall consensus among all DMs, thereby increasing the possibility of reaching a consensus. Subsequently, the aggregation result is defuzzified using the prevalent center-of-gravity method. The PCPA-FAHP approach was applied to a supplier selection problem to validate its effectiveness. According to the experimental results, the PCPA-FAHP approach not only successfully found out the partial consensus among the DMs, but also shrunk the widths of the estimated fuzzy weights to enhance the precision of the FAHP analysis.

2013 ◽  
Vol 315 ◽  
pp. 206-210 ◽  
Author(s):  
Amir Hossein Azadnia ◽  
Pezhman Ghadimi ◽  
Muhamad Zameri Mat Saman ◽  
Kuan Yew Wong ◽  
Cathal Heavey

Supplier selection is one of the important processes in supply chain management. Regarding the emergence of sustainability issues in recent decades, companies have incorporated these issues in conventional supplier selection in order to meet governmental legislations and market demands. These issues have been noticed by various researchers. However, there are limited research activities which considered all aspects of sustainability for supplier selection problem as an integrated assessment. In this paper, an integrated approach of Fuzzy Analytical Hierarchy Process and fuzzy logic has been proposed in order to solve sustainable supplier selection problem. Fuzzy analytical hierarchy process has been used to calculate the weight of sustainable criteria and sub criteria. Then, fuzzy logic was utilized in order to assess the suppliers based on the weights acquired by Fuzzy analytical hierarchy process. Finally, a case study of petroleum industry has been carried out in order to show the validity of proposed approach.


2017 ◽  
Vol 23 (7) ◽  
pp. 926-942 ◽  
Author(s):  
Gul POLAT ◽  
Ekin ERAY ◽  
Befrin Neval BINGOL

Materials constitute a large proportion of the total project cost and the absence of right materials in the right quantities and quality on site when needed is one of the most commonly experienced causes of delays in construction projects. Although supplier selection is a strategic issue, contractors generally select suppliers based on their past experi­ences, which may result in selecting wrong suppliers. Supplier selection decision is generally made by multiple decision makers and is affected by several criteria. Therefore, selecting the right supplier among many alternatives considering several compromising and conflicting criteria is a multi-criteria group decision-making (MCGDM) problem. This paper proposes an integrated fuzzy MCGDM approach, which employs fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) together, for the supplier selection problem. In the proposed approach, fuzzy AHP is used to analyse the structure of the supplier selection problem and to determine the weights of the criteria, and the fuzzy TOPSIS method is employed to rank the alternative suppliers. The proposed approach is applied to a problem of selecting the most appropriate rail supplier and company management found the proposed decision approach satisfactory and implementable in future supplier selection problems.


2015 ◽  
Vol 28 (2) ◽  
pp. 218-242 ◽  
Author(s):  
Vinod Yadav ◽  
Milind Kumar Sharma

Purpose – The problem of supplier selection gets complicated when a company looks for various criteria to evaluate different suppliers. The decision criteria used for supplier selection process can be different for different organizations due to a large number of factors. Hence, it can be said that supplier selection is basically, a multiple criteria decision-making (MCDM) problem. The purpose of this paper is to propose a hybrid data envelopment analytical hierarchy process (DEAHP) approach to solve the supplier selection problem for an automobile company. Design/methodology/approach – In this study, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. Literature review suggested that majority of researches found it appropriate using DEA and AHP methodologies for supplier selection process; hence it is felt that a hybrid DEAHP would be a useful methodology to offer a MCDM model for supplier selection problem. Findings – First, the key criteria of the supplier selection problem for the company are identified. Then a model is developed and implemented for supplier selection using DEAHP approach. This study concluded that quality, cost and service are the most crucial criteria for an automobile company operational in a developing country like India. Sensitivity analysis further helped to evaluate suppliers based on each criterion. Research limitations/implications – As this analysis and findings are based on only one case study of an Indian automobile company, and this necessitates caution in interpreting the results. The limited number of interviewed managers in a company restricts the generalizability of the results. Though the company selected for this study is typical of developing country businesses, the findings of the paper may not be readily extensible to other companies. Second, this study used retrospective settings, based on the interviewed feedback after the events had occurred. This method naturally poses limitations due to respondent recall and the accuracy of information provided. Third, the problem chosen for this study is based in a single country context and further additional research will be required to examine if the findings could be extended to other automobile companies in other developing nations. Also in some cases technique used in the study may pose some extra computational efforts. Practical implications – This study points out the importance of the supplier selection problem. It provides key criteria for supplier selection in Indian context also proposes a framework to deal with multiple criteria. proposed model deals with two crucial criteria long term relationships and flexibility which were relatively less discussed and considered in the literature in past. Originality/value – The proposed MCDM model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment.


2021 ◽  
Vol 9 (02) ◽  
pp. 60-67
Author(s):  
Nur Kharisa Umami ◽  
Setyawan Wibisono

There are still many parents who do not have sufficient understanding in terms of toddler disease. One way to provide education is the availability of a system that can be used for consultation based on the symptoms of illness experienced by toddlers and the actions needed to overcome them. The system that will be built is an expert system that can relatively provide suggestions for solutions to children's health problems using the Case Based Reasoning (CBR) method. namely an expert system that uses case-based reasoning methods, namely looking for similarities of a disease compared to a disease that has existed before. In this study, the CBR method was combined with a weighting process using the pairwise comparison method which was within the scope of the AHP (Analytic Hierarchy Process) method. In comparing consultations with old diseases that already exist in the system, and looking for similarities from the comparison results, the Sorensen similarity algorithm is used. This study resulted in weights with 3 symptom categories, namely mild symptoms with a weight of 0.09, moderate symptoms with a weight of 0.24 and severe symptoms with a weight of 0.67 and will recommend several diseases with a similarity above 0.5 and diseases with a similarity below 0.5 will be entered into the revise table to find a solution.


Author(s):  
Toly Chen ◽  
Hsin-Chieh Wu

In the existing group decision-making fuzzy analytic hierarchy process (FAHP) methods, the consensus among experts has rarely been fully reached. To fill this gap, in this study, a pre-aggregation fuzzy collaborative intelligence (FCI)-based FAHP approach is proposed. In the proposed pre-aggregation FCI-based FAHP approach, fuzzy intersection is applied to aggregate experts’ pairwise comparison results if these pairwise comparison results overlap. The aggregation result is a matrix of polygonal fuzzy numbers. Subsequently, alpha-cut operations are applied to derive the fuzzy priorities of criteria from the aggregation result. The pre-aggregation FCI-based FAHP approach has been applied to select suitable alternative suppliers for a wafer foundry in Taiwan amid the COVID-19 pandemic. The experimental results revealed that the pre-aggregation FCI-based FAHP approach significantly reduced the uncertainty inherent in the decision-making process by deriving fuzzy priorities with very narrow ranges.


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