scholarly journals A Hybrid MCDM Model to Evaluate and Classify Outsourcing Providers in Manufacturing

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1962
Author(s):  
Ching-Fang Liaw ◽  
Wan-Chi Jackie Hsu ◽  
Huai-Wei Lo
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Operating Costs ◽  
Visual Rating ◽  
Proposed Model ◽  
Ideal Solutions ◽  
Four Levels ◽  
Criteria Importance ◽  
Outsourcing Strategies

It is a common practice for enterprises to use outsourcing strategies to reduce operating costs and improve product competitiveness. Outsourcing providers or operators need to be aware of environmental protection and make products comply with the restrictions of international environmental regulations. Therefore, this study proposes a set of multiple criteria decision-making (MCDM) approaches for systematic green outsourcing evaluation. First, a team of experts is established to discuss mutually dependent relationships among criteria, and the decision-making trial and evaluation laboratory (DEMATEL) technique is applied to generate subjective influential weights. Then, a large amount of data from outsourcing providers is collected, and the criteria importance through the intercriteria correlation (CRITIC) method is used to obtain the objective influential weights. Finally, a novel classifiable technique for ordering preference based on similarity to ideal solutions (classifiable TOPSIS) is proposed to integrate the performance of green outsourcing providers and classify them into four levels. The classifiable TOPSIS improves the shortcomings of conventional TOPSIS and establishes a visual rating diagram to help decision-makers to distinguish the performance of outsourcing providers more clearly. Taking a Taiwanese multinational machine tool manufacturer as an example, the performance of outsourcing providers related to manufacturing activities was investigated to demonstrate the effectiveness and applicability of this proposed model.

A novel FMEA model based on fuzzy multiple-criteria decision-making methods for risk assessment

2020 ◽  
Vol 33 (5) ◽  
pp. 881-904 ◽  
Author(s):  
Reza Fattahi ◽  
Reza Tavakkoli-Moghaddam ◽  
Mohammad Khalilzadeh ◽  
Nasser Shahsavari-Pour ◽  
Roya Soltani
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Decision Making ◽  
Failure Mode ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Content Type ◽  
Proposed Model ◽  
Priority Weights

PurposeRisk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.Design/methodology/approachIn this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.FindingsTo show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.Originality/valueTo the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.

Evaluating social sustainable development factors using multi-experts Z-fuzzy AHP

2020 ◽  
Vol 39 (5) ◽  
pp. 6181-6192
Author(s):  
Nurdan Tüysüz ◽  
Cengiz Kahraman
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Fuzzy Numbers ◽  
Fuzzy Ahp ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Ahp Method ◽  
Proposed Model ◽  
The Social ◽  
Degree Of Confidence

This study presents a multi-experts multiple criteria decision making approach for quantitatively evaluating social sustainable development factors. The proposed model which integrates Z-fuzzy numbers and fuzzy AHP enables to weight and rank social sustainable development factors, which may give guidance to many sustainable development researches. In addition to the first usage of the Z-fuzzy numbers for the weighting decision of social sustainable development factors, another contribution of the study is presenting the Z-fuzzy numbers integrated AHP method with multi-experts which can be useful in many problems and applications containing uncertainty. The most important advantage of the Z-fuzzy numbers integrated AHP method is that it allows the degree of confidence of decision makers to be included to the calculations. An application of the proposed approach is also presented for prioritizing the social sustainable development factors based on the experts’ evaluations together with a sensitivity analysis.

scholarly journals Model for ore deposits selection by using the fuzzy TOPSIS method

2020 ◽  
Vol 56 (1) ◽  
pp. 59-71
Author(s):  
G. Popović ◽  
D. Stanujkić ◽  
D. Karabašević ◽  
Z. Štirbanović
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Ore Deposits ◽  
Decision Makers ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Ambiguous Data

Decision-makers are often being faced with imprecise and ambiguous data. In such circumstances, the use of extended Multiple-Criteria Decision-Making (MCDM) method is more appropriate than the use of other classic decision-making techniques. This paper develops an evaluation model based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to help the selection of the appropriate ore deposit for exploitation in a fuzzy environment. The applicability of the proposed model is demonstrated with a real case study involving four alternative ore deposits, seven evaluation criteria, and 3 decision-makers.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

Learning from failures: Design improvements using a multiple criteria decision-making process

2003 ◽  
Vol 217 (4) ◽  
pp. 207-216 ◽  
Author(s):  
G G Davidson ◽  
A W Labib
Keyword(s):  
Decision Making ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Mathematical Representation ◽  
Analytic Hierarchy ◽  
Proposed Model ◽  
Invaluable Tool ◽  
History Of

This paper proposes a new concept of decision analysis based on a multiple criteria decision making (MCDM) process. This is achieved through the provision of a systematic and generic methodology for the implementation of design improvements based on experience of past failures. This is illustrated in the form of a case study identifying the changes made to Concorde after the 2000 accident. The proposed model uses the analytic hierarchy process (AHP) mathematical model as a backbone and integrates elements of a modified failure modes and effects analysis (FMEA). The AHP has proven to be an invaluable tool for decision support since it allows a fully documented and transparent decision to be made with full accountability. In addition, it facilitates the task of justifying improvement decisions. The paper is divided as follows: the first section presents an outline of the background to the Concorde accident and its history of related (non-catastrophic) malfunctions. The AHP methodology and its mathematical representation are then presented with the integrated FMEA applied to the Concorde accident. The case study arrives at the same conclusion as engineers working on Concorde after the accident: that the aircraft may fly again if the lining of the fuel tanks are modified.

Constructing a Hierarchy and Simulation Model to Assess Digital Recorder Sensor System

2012 ◽  
Vol 263-266 ◽  
pp. 857-860
Author(s):  
Kuang Jung Tseng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Safety Evaluation ◽  
Decision Makers ◽  
Sensor System ◽  
Model Following ◽  
Proposed Model ◽  
Digital Recorder ◽  
Decision Making Model

This work presents group decision making model, following a university safety evaluation to demonstrate the effectiveness of the proposed model. Importantly, the proposed model can assist university decision makers to buy the feasibility of digital recorder sensor system, making it highly applicable for academic and commercial purposes.

An Application of the Integrated IBA-TOPSIS Model in Supplier Selection

2015 ◽  
Vol 7 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Ksenija Mandić ◽  
Boris Delibašić ◽  
Dragan Radojević
Keyword(s):  
Decision Making ◽  
Boolean Algebra ◽  
Supplier Selection ◽  
Selection Process ◽  
Real Life ◽  
Decision Makers ◽  
Proposed Model ◽  
Qualitative Variables ◽  
Hidden Knowledge ◽  
Multi Attribute Decision Making

The supplier selection process attracted a lot of attention in the business management literature. This process takes into consideration several quantitative and qualitative variables and is usually modeled as a multi-attribute decision making (MADM) problem. A recognized shortcoming in the literature of classical MADM methods is that they don't permit the identification of interdependencies among attributes. Therefore, the aim of this study is to propose a model for selecting suppliers of telecommunications equipment that includes the interaction between attributes. This interaction can model the hidden knowledge needed for efficient decision-making. To model interdependencies among attributes the authors use a recently proposed consistent fuzzy logic, i.e. interpolative Boolean algebra (IBA). For alternatives ranking they use the classical MADM method TOPSIS. The proposed model was evaluated on a real-life application. The conclusion is that decision makers were able to integrate their reasoning into the MADM model using interpolative Boolean algebra.

scholarly journals A Hybrid Network Model to Extract Key Criteria and Its Application for Brand Equity Evaluation

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Chin-Yi Chen ◽  
Chung-Wei Li
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Brand Equity ◽  
Program Planning ◽  
Evaluation Criteria ◽  
Practical Method ◽  
Decision Makers ◽  
Hybrid Network ◽  
Proposed Model ◽  
Equity Evaluation

Making a decision implies that there are alternative choices to be considered, and a major challenge of decision-making is to identify the adequate criteria for program planning or problem evaluation. The decision-makers’ criteria consists of the characteristics or requirements each alternative must possess and the alternatives are rated on how well they possess each criterion. We often use criteria developed and used by different researchers and institutions, and these criteria have similar means and can be substituted for one another. Choosing from existing criteria offers a practical method to engineers hoping to derive a set of criteria for evaluating objects or programs. We have developed a hybrid model for extracting evaluation criteria which considers substitutions between the criteria. The model is developed based on Social Network Analysis and Maximum Mean De-Entropy algorithms. In this paper, the introduced methodology will also be applied to analyze the criteria for assessing brand equity as an application example. The proposed model demonstrates that it is useful in planning feasibility criteria and has applications in other evaluation-planning purposes.

scholarly journals Fuzzy Linear Physical Programming for Multiple Criteria Decision-Making Under Uncertainty

2015 ◽  
Vol 11 (1) ◽  
pp. 26 ◽  
Author(s):  
Ahmed ElSayed ◽  
Elif Kongar ◽  
Surendra M. Gupta
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Decision Maker ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Making Under Uncertainty ◽  
Physical Programming ◽  
Fuzzy Environment ◽  
Linear Physical Programming ◽  
Proposed Model

<p>This paper presents a newly developed fuzzy linear physical programming (FLPP) model that allows the decision maker to introduce his/her preferences for multiple criteria decision making in a fuzzy environment. The major contribution of this research is to generalize the current models by accommodating an environment that is conducive to fuzzy problem solving. An example is used to evaluate, compare and discuss the results of the proposed model.</p>

scholarly journals Multiple Criteria Decision Making Based on Probabilistic Interval-Valued Hesitant Fuzzy Sets by Using LP Methodology

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
M. Sarwar Sindhu ◽  
Tabasam Rashid ◽  
Agha Kashif ◽  
Juan Luis García Guirao
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Real Life ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Occurrence Probability ◽  
Hesitant Fuzzy Sets ◽  
Life Problems ◽  
Interval Valued

Probabilistic interval-valued hesitant fuzzy sets (PIVHFSs) are an extension of interval-valued hesitant fuzzy sets (IVHFSs) in which each hesitant interval value is considered along with its occurrence probability. These assigned probabilities give more details about the level of agreeness or disagreeness. PIVHFSs describe the belonging degrees in the form of interval along with probabilities and thereby provide more information and can help the decision makers (DMs) to obtain precise, rational, and consistent decision consequences than IVHFSs, as the correspondence of unpredictability and inaccuracy broadly presents in real life problems due to which experts are confused to assign the weights to the criteria. In order to cope with this problem, we construct the linear programming (LP) methodology to find the exact values of the weights for the criteria. Furthermore these weights are employed in the aggregation operators of PIVHFSs recently developed. Finally, the LP methodology and the actions are then applied on a certain multiple criteria decision making (MCDM) problem and a comparative analysis is given at the end.

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