scholarly journals Fusing Multi-Attribute Decision Models for Decision Making to Achieve Optimal Product Design

2020 ◽  
Vol 45 (4) ◽  
pp. 305-337
Author(s):  
Olayinka Mohammed Olabanji ◽  
Khumbulani Mpofu
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Design Concept ◽  
Design Features ◽  
Decision Matrix ◽  
Analytic Hierarchy ◽  
Design Concepts ◽  
Fuzzy Vikor ◽  
Design Alternatives ◽  
Optimal Product Design

AbstractManufacturers need to select the best design from alternative design concepts in order to meet up with the demand of customers and have a larger share of the competitive market that is flooded with multifarious designs. Evaluation of conceptual design alternatives can be modelled as a Multi-Criteria Decision Making (MCDM) process because it includes conflicting design features with different sub features. Hybridization of Multi Attribute Decision Making (MADM) models has been applied in various field of management, science and engineering in order to have a robust decision-making process but the extension of these hybridized MADM models to decision making in engineering design still requires attention. In this article, an integrated MADM model comprising of Fuzzy Analytic Hierarchy Process (FAHP), Fuzzy Pugh Matrix and Fuzzy VIKOR was developed and applied to evaluate conceptual designs of liquid spraying machine. The fuzzy AHP was used to determine weights of the design features and sub features by virtue of its fuzzified comparison matrix and synthetic extent evaluation. The fuzzy Pugh matrix provides a methodical structure for determining performance using all the design alternatives as basis and obtaining aggregates for the designs using the weights of the sub features. The fuzzy VIKOR generates the decision matrix from the aggregates of the fuzzified Pugh matrices and determine the best design concept from the defuzzified performance index. At the end, the optimal design concept is determined for the liquid spraying machine.

Adopting hybridized multicriteria decision model as a decision tool in engineering design

2019 ◽  
Vol 18 (2) ◽  
pp. 451-479 ◽  
Author(s):  
Olayinka Mohammed Olabanji ◽  
Khumbulani Mpofu
Keyword(s):  
Decision Making ◽  
Optimal Design ◽  
Engineering Design ◽  
Decision Tool ◽  
Design Features ◽  
Decision Matrix ◽  
Content Type ◽  
Multicriteria Decision ◽  
Design Concepts ◽  
Left And Right

Purpose The purpose of this paper is to determine the suitability of adopting hybridized multicriteria decision-making models as a decision tool in engineering design. This decision tool will assist design engineers and manufacturers to determine a robust design concept before simulation and manufacturing while all the design features and sub features would have been identified during the decision-making process. Design/methodology/approach Fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) are hybridized and applied to obtain optimal design of a reconfigurable assembly fixture (RAF) from a set of alternative design concepts. Design features and sub features associated with the RAF are identified and compared using fuzzified pairwise comparison matrices to obtain weights of their relative importance in the optimal design. The FAHP obtained the fuzzy synthetic extent (FSE) values of the design features and sub features. The FSE values are used as weights of the design features and sub features in generating the decision matrix. FTOPSIS and FTOPSIS based on left and right scores were adopted to predict effects of the weights. Results were obtained for normalized and unnormalized weights of the design features and its effects on the relative closeness coefficients of the design alternatives. Findings The improved performance of the FTOPSIS based on left and right scores is due to the involvement of the left and right scores of weights of the design features in the computation of distances from positive and negative ideal solutions. Embedding the weights of the design features in the normalized decision matrix before estimating the distances of the design concepts from ideal solutions reduces the dependency of the closeness coefficients on the weights of the design features. This also decreases the difference in the final values of the design concepts. In essence, the weights of the design features have an impact in the closeness coefficient. There is reduction in the closeness coefficients of the design concepts due to normalization of the weights of the design features. However, normalizing the weights of the design features did not affect the variations in the final values of the design concept. As the final value of the design concepts can be influenced by the normalized weights of the design features, it can be implied that normalization of weights of the sub features will also affect the decision matrix. The study has been able to proof that hybridizing FAHP and FTOPSIS can produce effective results for decisions on optimal design by the application of FTOPSIS based on left and right scores rather than the general FTOPSIS. Originality/value This research develops a hybridized multicriteria decision-making model for decision-making in engineering design. It presents a detailed extension of hybridized FAHP and FTOPSIS based on left and right scores as a useful tool for considering the relative importance of design features and sub features in optimal design selection.

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

Probabilistic Linguistic Analytic Hierarchy Process and Its Application on the Performance Assessment of Xiongan New Area

2018 ◽  
Vol 17 (06) ◽  
pp. 1693-1724 ◽  
Author(s):  
Wanying Xie ◽  
Zeshui Xu ◽  
Zhiliang Ren ◽  
Hai Wang
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Uncertain Information ◽  
Decision Matrix ◽  
Analytic Hierarchy ◽  
Decision Tools ◽  
Probabilistic Linguistic Term Set ◽  
Complex Decision Making ◽  
The Individual ◽  
Hierarchy Process

Analytic Hierarchy Process (AHP) is one of the most favorable decision tools for dealing with complex decision-making problems. Probabilistic linguistic term set (PLTS) is an up-to-date tool to deal with uncertain information in the decision-making process. In this paper, we extend the AHP to the probabilistic linguistic environment for perfecting the modeling ability of AHP in various decision-making problems. In order to apply the PLTSs to the AHP properly, we first redefine the probabilistic linguistic comparison matrix (PLCM) and propose a new consistency index. Then, we propose a new approach to check and improve the consistency of the PLCMs. After that, we aggregate the individual PLCMs into the collective PLCM and derive the priorities of the collective PLCM. Finally, we combine the priorities with the decision matrix to complete the ranking of alternatives, and a case concerning the performance assessments of three new areas is given and the comparative analysis about the results is performed to demonstrate the feasibility of the proposed method.

Fuzzy Analytic Hierarchy Process and Its Application to E-Marketplace Selection

2013 ◽  
pp. 26-44 ◽  
Author(s):  
Beyza Ahlatcioglu Ozkok ◽  
Elisa Pappalardo
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Multi Criteria Decision Making ◽  
Linguistic Variables ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Electronic Parts ◽  
Hierarchy Process

Making decisions is a part of daily life. The nature of decision-making includes multiple and usually conflicting criteria. Multi Criteria Decision-Making (MCDM) problems are handled under two main headings: Multi Attribute Decision Making (MADM) and Multi Objective Decision Making (MODM). Analytic Hierarchy Process (AHP) is a widely used multi-criteria decision making approach and has successfully been applied to many practical problems. Traditional AHP requires exact or crisp judgments (numbers). However, due to the complexity and uncertainty involved in real world decision problems, decision makers might be more reluctant to provide crisp judgments than fuzzy ones. Furthermore, even when people use the same words, individual judgments of events are invariably subjective, and the interpretations that they attach to the same words may differ. This is why fuzzy numbers and fuzzy sets have been introduced to characterize linguistic variables. Here, the authors overview the most known fuzzy AHP approaches and their application, and they present a case study to select an e-marketplace for a firm, which produces and sells electronic parts of computers in Turkey.

scholarly journals A Multicriteria Decision-Making Approach Based on Fuzzy AHP with Intuitionistic 2-Tuple Linguistic Sets

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Shahzad Faizi ◽  
Tabasam Rashid ◽  
Sohail Zafar
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Preference Relation ◽  
Multicriteria Decision Making ◽  
Transformation Mechanism ◽  
Analytic Hierarchy ◽  
Multicriteria Decision ◽  
Linguistic Representation ◽  
Representation Model ◽  
Linguistic Preference Relation

In the modern literature related to linguistic decision-making, the 2-tuple linguistic representation model and its useful applications in various fields have been extensively studied and used during the last decade. Recently, some useful multicriteria decision-making (MCDM) methods have been introduced based on fuzzy analytic hierarchy process (AHP) for 2-tuple linguistic representation model. By keeping in mind the importance of this linguistic model, in this paper, we introduce a fuzzy AHP methodology for intuitionistic 2-tuple linguistic sets (I2TLSs) which is a useful extension of the 2-tuple linguistic representation model. This study is comprised of four stages. In the first stage, we define some operational laws for I2TL elements (I2TLEs) and prove some related important properties. In the second stage, intuitionistic 2-tuple linguistic preference relation (I2TLPR) and multiplicative I2TLPR are defined using I2TLSs. In the 3rd stage, a transformation mechanism is introduced which can transform an I2TLPR to a corresponding intuitionistic preference relation (IPR) and vice versa. In the fourth stage, an approach is proposed for checking the consistency of an I2TLPR and presented a method to repair the inconsistent one by using the proposed transformation mechanism. Finally, a numerical example is given and comparative analysis is carried out with the TOPSIS method to verify the validity of the proposed method.

Fuzzy Ratings and Crisp Feedback in Fuzzy AHP for Supporting Human Decision Making

2006 ◽  
Vol 10 (2) ◽  
pp. 219-224 ◽  
Author(s):  
Toshiyuki Yamashita ◽  
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Psychological Effects ◽  
Analytic Hierarchy ◽  
Human Decision ◽  
Hierarchy Process

Analytic Hierarchy Process (AHP) is one of the most popular tools for supporting human decision making, and several fuzzy extensions of AHP have been proposed. The present study investigated psychological effects of both fuzzy ratings in fuzzy AHP and crisp feedback of the results from fuzzy AHP. The results suggest that fuzzy ratings could incorporate the fuzziness of a person’s feelings in his/her decision making. The results also suggest that crisp feedback, which exaggerates the superiority of only one alternative or the differences among the alternatives, could help a person to make his/her decision, especially when being deeply puzzled about his/her choice.

scholarly journals Refractured Well Selection for Multicriteria Group Decision Making by Integrating Fuzzy AHP with Fuzzy TOPSIS Based on Interval-Typed Fuzzy Numbers

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Tiejun Li ◽  
Jianhua Jin ◽  
Chunquan Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Fuzzy Topsis ◽  
Selection Problem ◽  
Triangular Fuzzy Numbers ◽  
Analytic Hierarchy ◽  
Multicriteria Group Decision Making

Multicriteria group decision making (MCGDM) research has rapidly been developed and become a hot topic for solving complex decision problems. Because of incomplete or non-obtainable information, the refractured well-selection problem often exists in complex and vague conditions that the relative importance of the criteria and the impacts of the alternatives on these criteria are difficult to determine precisely. This paper presents a new model for MCGDM by integrating fuzzy analytic hierarchy process (AHP) with fuzzy TOPSIS based on interval-typed fuzzy numbers, to help group decision makers for well-selection during refracturing treatment. The fuzzy AHP is used to analyze the structure of the selection problem and to determine weights of the criteria with triangular fuzzy numbers, and fuzzy TOPSIS with interval-typed triangular fuzzy numbers is proposed to determine final ranking for all the alternatives. Furthermore, the algorithm allows finding the best alternatives. The feasibility of the proposed methodology is also demonstrated by the application of refractured well-selection problem and the method will provide a more effective decision-making tool for MCGDM problems.

scholarly journals COMPARISON OF DIFFERENT FUZZY AHP METHODOLOGIES IN RISK ASSESSMENT

2017 ◽  
Vol 2 ◽  
pp. 137 ◽  
Author(s):  
Andrejs Radionovs ◽  
Oleg Uzhga-Rebrov
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fuzzy Ahp ◽  
Multiple Criteria Decision Making ◽  
Environmental Risks ◽  
Assessment Process ◽  
Analytic Hierarchy ◽  
Risk Assessment Process ◽  
Risks Assessment ◽  
Hierarchy Process

Being able to evaluate risks is an important task in many areas of human activity: economics, ecology, etc. Usually, environmental risk assessment is carried out on the basis of multiple and sometimes conflicting factors. Using multiple criteria decision-making (MCDM) methodology is one of the possible ways to solve the problem. Methodologies of analytic hierarchy process (AHP) are the most commonly used MCDM methods, which combine subjective and personal preferences in risk assessment process. However, AHP involves human subjectivity, which introduces vagueness type of uncertainty and requires the usage of decision making under those uncertainties. In this paper it was considered to deal with uncertainty by using the fuzzy-based techniques. However, nowadays there exist multiple Fuzzy AHP methodologies developed by different authors. In this paper, these Fuzzy AHP methodologies will be compared, and the most appropriate Fuzzy AHP methodology for the application in case of environmental risks assessment will be offered on the basis of this comparison.

scholarly journals A Novel Portfolio Based on Interval-Valued Intuitionistic Fuzzy AHP with Improved Combination Weight Method and New Score Function

2021 ◽  
Author(s):  
Xue Deng ◽  
Fengting Geng ◽  
Jianxin Yang
Keyword(s):  
Mathematical Proof ◽  
Fuzzy Ahp ◽  
Score Function ◽  
Decision Matrix ◽  
Entropy Weight ◽  
Analytic Hierarchy ◽  
Weighting Method ◽  
Score Functions ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

Abstract The classical Analytic Hierarchy Process (AHP) requires an exact value to compare the relative importance of two attributes, but experts often can not obtain an accurate assessment of every attribute in the decision-making process, there are always some uncertainty and hesitation. Compared with classical AHP, our new defined interval-valued intuitionistic fuzzy AHP has accurately descripted the vagueness and uncertainty. In decision matrix, the real numbers are substituted by fuzzy numbers. In addition, each expert will make different evaluations according to different experiences for each attribute in the subjective weighting method, which neglects objective factors and then generates some deviations in some cases. This paper provides two ways to make up for this disadvantage. On the one hand, by combining the interval-valued intuitionistic fuzzy AHP with entropy weight, an improved combination weighting method is proposed, which can overcome the limitations of unilateral weighted method only considering the objective or subjective factors. On the other hand, a new score function is presented by adjusting the parameters, which can overcome the invalidity of some existing score functions. In theory, some theorems and properties for the new score functions are given with strictly mathematical proof to validate its rationality and effectiveness. In application, a novel fuzzy portfolio is proposed based on the improved combination weighted method and new score function. A numerical example shows that these results of our new score function are consistent with those of most existing score functions, which verifies that our model is feasible and effective.

Multi-Attribute Decision Making Using Interval Type-2 Fuzzy AHP and Its Application on Borsa Istanbul (BIST)

2021 ◽  
pp. 30-56
Author(s):  
Beyza Ahlatcioglu Ozkok ◽  
Hale Gonce Kocken
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Ahp ◽  
Short Review ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Interval Type

Analytic hierarchy process (AHP) is a widely used multi-attribute decision-making (MADM) approach. Due to the complexity and uncertainty involved in real world problems, decision makers might be prefer to make fuzzy judgments instead of crisp ones. Furthermore, even when people use the same words, individual judgments of events are invariably subjective, and the interpretations that they attach to the same words may differ. This is why fuzzy numbers has been introduced to characterize linguistic variables. Fuzzy AHP methods have recently been extended by using type-2 fuzzy sets. Type-2 fuzzy set theory incorporates the uncertainty of membership functions into the fuzzy set theory. In this chapter, the authors firstly provide a short review on applications of interval type-2 fuzzy AHP on MADM problems. Then, they present a very efficient MADM technique, interval type-2 fuzzy AHP, to solve the portfolio selection problem that is to decide which stocks are to be chosen for investment and in what proportions they will be bought. And finally, they provided a case study on BIST.

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