Fuzzy multicriteria decision-making-based optimal Zn–Al alloy selection in corrosive environment

2020 ◽  
Vol 111 (11) ◽  
pp. 953-963
Author(s):  
Ankur V. Bansod ◽  
Awanikumar P. Patil ◽  
Kanak Kalita ◽  
B. D. Deshmukh ◽  
Nilay Khobragade
Keyword(s):  
Decision Making ◽  
Weight Loss ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Al Alloy ◽  
Ideal Solution ◽  
Corrosive Environment ◽  
Multicriteria Decision ◽  
Al Content ◽  
The Ideal

Abstract Suitable material selection with emphasis on a specific property or application is an indispensable part of engineering sciences. It is a complex process that involves multiple criteria and often multiple decision makers. The tendency of decision makers to specify their preference in terms of imprecise qualitative statements like ‘good’, ‘bad’ etc. poses a further challenge. Thus, in this research, a comprehensive multicriteria decision-making study was conducted to select the optimal Zn-Al alloy based on performance in a corrosive environment. Four variants of technique for order of preference by similarity to the ideal solution were used to perform the multicriteria decision-making analysis. Group decision and imprecise decision making is handled by incorporating the fuzzy theory concept in a technique for order of preference by similarity to the ideal solution. The effect of addition of aluminium to zinc was studied by examination of microstructure, hardness, and corrosion behaviour. The result indicates that an increase in Al content increases the formation of dendrites. The dendrites were rich in the α phase, which results in an increase in hardness. An increase in Al content in Zn (Zn-22Al and Zn-55Al) results in the uniform distribution of the a phase in the microstructure and reduction of non-equilibrium phases. The potentiodynamic polarisation test revealed that an increase in Al in the alloy decreases the corrosion current density. The weight loss test carried out to validate the potentiodynamic test findings exhibited higher weight loss in pure Zn and lowest in Zn-55Al. Similar results were observed in the salt spray test. The multicriteria decision-making analysis revealed that Zn-55Al is the most suitable alloy in a corrosive environment among the tested alloys.

scholarly journals Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

2021 ◽  
Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Programming Model ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Multicriteria Decision ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Decision Making Models ◽  
Best Worst Method

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.

scholarly journals A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Bowen Wang ◽  
Haitao Xiong ◽  
Chengrui Jiang
Keyword(s):  
Decision Making ◽  
Fuzzy Theory ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Location Selection ◽  
Logistics Center ◽  
Multicriteria Decision ◽  
Model Based ◽  
Center Location ◽  
Decision Making Model

As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

scholarly journals A Study of Multicriteria Decision Making for Supplier Selection in Automotive Industry

2013 ◽  
Vol 2013 ◽  
pp. 1-22 ◽  
Author(s):  
Nadia Jamil ◽  
Rosli Besar ◽  
H. K. Sim
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Supplier Selection ◽  
Selection Process ◽  
Multicriteria Decision Making ◽  
Ideal Solution ◽  
Fuzzy Analytical Hierarchy Process ◽  
Automotive Manufacturing ◽  
Multicriteria Decision ◽  
Hierarchy Process

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.

scholarly journals A Comparative Study between GLP and GBWM

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Reda M. S. Abdulaal ◽  
Omer A. Bafail
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Comparative Study ◽  
Simplex Method ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
The Other ◽  
Ideal Solution ◽  
Linguistic Variables ◽  
Best Worst Method

When decision-makers’ judgments are uncertain, they often express their opinions using grey linguistic variables. Once used, the data often retains its grey nature throughout all subsequent decision-making iterations. Multicriteria decision-making (MCDM) is a tool used when making complicated decisions and in circumstances where several criteria require evaluation to choose the most desirable option. Grey data serves as the basis for several MCDM methods. This paper compares two MCDM methods, Grey-Linear-Programming (GLP) and Grey-Best-Worst-Method (GBWM), in terms of the weights of decision criteria and their rankings. Moreover, Grey-The Technique for Order of Preference by Similarity to Ideal Solution (GTOPSIS) was used to rank the weights of the two methods. Study findings demonstrated that GBWM requires more mathematical calculations than GLP, based on linear programming's classic simplex method. On the other hand, when GTOPSIS follows GLP, the alternative rank does not change compared to when GTOPSIS followed GBWM. For the applications used in this comparison, GLP procedure is considered simpler than GBWM procedure.

scholarly journals Supportiveness of Low-Carbon Energy Technology Policy Using Fuzzy Multicriteria Decision-Making Methodologies

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1178 ◽  
Author(s):  
Konstantinos Kokkinos ◽  
Vayos Karayannis
Keyword(s):  
Decision Making ◽  
Swot Analysis ◽  
Technology Policy ◽  
Multicriteria Decision Making ◽  
Clean Energy ◽  
Policy Formulation ◽  
Ideal Solution ◽  
Low Carbon ◽  
Multicriteria Decision ◽  
Low Carbon Energy

The deployment of low-carbon energy (LCE) technologies and management of installations represents an imperative to face climate change. LCE planning is an interminable process affected by a multitude of social, economic, environmental, and health factors. A major challenge for policy makers is to select a future clean energy strategy that maximizes sustainability. Thus, policy formulation and evaluation need to be addressed in an analytical manner including multidisciplinary knowledge emanating from diverse social stakeholders. In the current work, a comparative analysis of LCE planning is provided, evaluating different multicriteria decision-making (MCDM) methodologies. Initially, by applying strengths, weaknesses, opportunities, and threats (SWOT) analysis, the available energy alternative technologies are prioritized. A variety of stakeholders is surveyed for that reason. To deal with the ambiguity that occurred in their judgements, fuzzy goal programming (FGP) is used for the translation into fuzzy numbers. Then, the stochastic fuzzy analytic hierarchical process (SF-AHP) and fuzzy technique for order performance by similarity to ideal solution (F-TOPSIS) are applied to evaluate a repertoire of energy alternative forms including biofuel, solar, hydro, and wind power. The methodologies are estimated based on the same set of tangible and intangible criteria for the case study of Thessaly Region, Greece. The application of FGP ranked the four energy types in terms of feasibility and positioned solar-generated energy as first, with a membership function of 0.99. Among the criteria repertoire used by the stakeholders, the SF-AHP evaluated all the criteria categories separately and selected the most significant category representative. Finally, F-TOPSIS assessed these criteria ordering the energy forms, in terms of descending order of ideal solution, as follows: solar, biofuel, hydro, and wind.

Decision Making Model Based on the Z-Information

2020 ◽  
Vol 26 (11) ◽  
pp. 625-630
Author(s):  
O. M. Poleshchuk ◽  
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Decision Models ◽  
Probabilistic Assessment ◽  
Multicriteria Decision ◽  
Numerical Example ◽  
Model Based ◽  
Definition Of ◽  
Decision Making Model ◽  
The Ideal

A model of multicriteria decision making is developed taking into account the reliability of the data obtained. To formalize the information containing the data and assess their reliability, Z-numbers are used, the definition of which was given by Lotfie Zadeh in 2011. Most of the well-known decision models based on Z-numbers are limited by the assumption of a probabilistic assessment of the reliability of the data, which significantly narrows the scope of these models. This article partially removes the restrictive requirements when working with Z-numbers. For components of Z-numbers, aggregate indicators are calculated using a-cuts, based on which the similarity indicator between Z-numbers is determined. Choosing the best alternative is based on the minimum indicator of similarity with the ideal alternative. A numerical example is presented that shows the operation of the model and its effectiveness under conditions of multi-criteria selection.

scholarly journals Sistem Pendukung Keputusan Rekomendasi Pemberian Remisi Pada Narapidana Menggunakan Metode Topsis (Studi Kasus Pada Lembaga Pemasyarakatan Klas II-A Palu)

2019 ◽  
Vol 1 (1) ◽  
pp. 11
Author(s):  
A.Y. Erwin Dodu ◽  
Yusuf Anshori ◽  
Dennis Tandi Limbong
Keyword(s):  
Decision Making ◽  
Social Life ◽  
Multicriteria Decision Making ◽  
Health Condition ◽  
Ideal Solution ◽  
Correctional Institution ◽  
Leadership Skill ◽  
Order Preference ◽  
The Republic ◽  
The Ideal

Remission is a reduction of criminal punishment given to prisoners who have been regulated in the laws of the Republic of Indonesia. The process of giving scores to inmates in Class IIA Palu Correctional Institution with certain criteria aims to facilitate the employees of Palu Class IIA to get recommendation of remission of prisoners. The decision support system in this research uses Technique for Order Preference method by Similiarity to Ideal Solution ( TOPSIS) which is one of the multicriteria decision-making methods, where the basic idea of this method is that the chosen alternative has the closest distance to the ideal solution and the furthest from the ideal negative solution. In determining the inmates who receive remission recommendation in Correctional Institution Class IIA Palu there are 6 criteria which become the basis of decision making such as health condition, special skill and leadership skill, social life, never breaking order and not being a recidivist. The final result in this study is the result of calculation of proximity relative to the ideal solution that is sorted from the highest value to the lowest value so that employees of Correctional Institution Class IIA can easily take a decision on remission recommendations by looking at the results of the sorting

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