scholarly journals A New Methodology of Multicriteria Decision-Making in Supplier Selection Based onZ-Numbers

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Bingyi Kang ◽  
Yong Hu ◽  
Yong Deng ◽  
Deyun Zhou

Supplier selection is a significant issue of multicriteria decision-making (MCDM), which has been heavily studied with classical fuzzy methodologies, but the reliability of the knowledge from domain experts is not efficiently taken into consideration.Z-number introduced by Zadeh has more power to describe the knowledge of human being with uncertain information considering both restraint and reliability. In this paper, a methodology for supplier selection usingZ-numbers is proposed considering information transformation. It includes two parts: one solves the issue of how to convertZ-number to the classic fuzzy number according to the fuzzy expectation; the other solves the problem of how to get the optimal priority weight for supplier selection with genetic algorithm (GA), which is an efficient and flexible method for calculating the priority weight of the judgement matrix. Finally, an example for supplier selection is used to illustrate the effectiveness the proposed methodology.

2013 ◽  
Vol 2013 ◽  
pp. 1-22 ◽  
Author(s):  
Nadia Jamil ◽  
Rosli Besar ◽  
H. K. Sim

This paper is designed to present the effectiveness of group multicriteria decision making in automotive manufacturing company focusing on the selection of suppliers in Malaysia. The process of selecting suppliers is one of the most critical and challenging endeavor in any supply chain management. There are five decision making tools being analyzed in this study, namely, analytical hierarchy process (AHP), fuzzy analytical hierarchy process (FAHP), technique for order performance by similarity to ideal solution (TOPSIS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), and fuzzy analytical hierarchy process integrated with fuzzy technique for order performance by similarity to ideal solution (FAHPiFTOPSIS). The scores of ranking among the suppliers in each MCDM tools (AHP, FAHP, TOPSIS, FTOPSIS, and FAHPiFTOPSIS) show significantly comparable variation. Scores of the best supplier is then compared to the lowest supplier for all MCDM tools whereby this reflects that the highest percentage goes to TOPSIS with scoring of 79.37%. On the contrary, FAHPiFTOPSIS demonstrated the lowest score variation of 22.42% which indicates that FAHPiFTOPSIS is able to eliminate biasness in supplier selection process.


2011 ◽  
Vol 52-54 ◽  
pp. 1868-1872
Author(s):  
Liang Liang ◽  
Ren Yan Jiang ◽  
Yin Liang

It is difficult to obtain the correct criteria weights with uncertain information in the multicriteria decision-making. Many methods depend on the subjective estimate. Therefore, a method is presented to evaluate the samples ranking only need the importance order of criteria. It evaluates firstly the overall ranking scores of samples based on the graphical classification and multicriteria hierarchical integrated methods. Subsequently, the relation model between the criteria scores and overall ranking scores of samples is built by linear regression. Finally, a fincial credit loan decision-making problem is presented to describe the way of the multicriteria decisiion making process. The analysis to compare with the AHP method illustrates the proposed method is objective and effective.


2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Qinghua Pang ◽  
Tiantian Yang ◽  
Mingzhen Li ◽  
Yi Shen

Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach.


Author(s):  
Manzoor Hussain

Fuzzy entropy is being used to measure the uncertainty with high precision and accuracy than classical crisp set theory. It plays a vital role in handling complex daily life problems involving uncertainty. In this manuscript, we first review several existing entropy measures and then propose novel entropy to measure the uncertainty of a fuzzy set. We also construct an axiomatic definition based on the proposed entropy measure. Numerical comparison analysis is carried out with existing entropies to show the reliability and practical applicability of our proposed entropy measure. Numerical results show that our suggested entropy is reasonable and appropriate in dealing with vague and uncertain information. Finally, we utilize our proposed entropy measure to construct fuzzy TOPSIS (Technique for Ordering Preference by Similarity to Ideal Solution) method to manage Multicriteria decision-making problems related to daily life settings. The final results demonstrate the practical effectiveness and applicability of our proposed entropy measure


2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shi Yin ◽  
Baizhou Li ◽  
Hengmin Dong ◽  
Zeyu Xing

Nowadays, due to the lack of natural resources and environment problems which have been appearing increasingly, green building is more and more involved in the construction industry. The evaluation and selection of green supplier are a significant part of the development of green building. In this paper, we propose a new dynamic multicriteria decision-making approach in construction projects under time sequence to deal with these problems. First, the paper establishes 4 main criteria and 17 subcriteria for green supplier selection in construction projects. Then, a method considering interaction between criteria and the influence of constructors subjective preference and objective criteria information is proposed. It uses the interval-valued intuitionistic fuzzy geometric weighted Heronian means (IVIFGWHM) operator and multitarget nonlinear programming model to calculate the comprehensive evaluation results of potential green suppliers. The proposed method is much easier for constructors to select green supplier and make the localization of green supplier more practical and accurate in construction projects. Finally, a case study about a green building project is given to verify practicality and effectiveness of the proposed approach.


Mathematics ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 981 ◽  
Author(s):  
Wang ◽  
Thanh ◽  
Chyou ◽  
Lin ◽  
Nguyen

To be able to compete in the domestic plastic industry, small and medium-sized enterprises producing plastic need to proactively find the supply of raw materials, avoiding shortages like in the previous years. Purchasing is extremely important and will create a competitive advantage with competitors in the market, so finding suppliers will determine the success in the later stages of the production chain. With the development of the current information system, selection and evaluation have become important in order to achieve effective decision-making through optimal options. In this study, the authors provide a new approach for decision-makers in evaluating and selecting suppliers, which is formulated based on the supply chain operation reference (SCOR) model, fuzzy analytic network process (FANP), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The contribution of this research is to propose a multicriteria decision-making model (MCDM) for raw material supplier selection in the plastic industry. This research also provided a useful guideline for supplier selection in other industry.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Liguo Fei ◽  
Yong Hu ◽  
Fuyuan Xiao ◽  
Luyuan Chen ◽  
Yong Deng

Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, aD-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, calledDnumbers. TheD-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method,Dnumbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposedD-TOPSIS method.


Author(s):  
Juan Fernando Herrera Guardiola ◽  
Rafaela Ferreira Lopes ◽  
João Carlos Correa Baptista Soares de Mello ◽  
Flávio Castro da Silva

Macbeth model is a multicriteria tool for the multicriteria decision making that has been used in different projects and studies of renewable energies. The purpose of this paper was apply the software Macbeth for the evaluation of canola, corn, palm and soy crops taking in to account technician, environmental and economic criterias and their weights. Canola crop was the best option for the biodiesel production, with a global score of 74 points because of their good score in environmental criterias, wich had a higher weight than the other criterias. Corn crop was the second positioned, presenting good results in all criterias, followed by palm crop. The final one was soy crop with 36,67 points in this analysis.


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