scholarly journals Selecting Doffing Tube Components for Rotor-Spun Yarn for Weft Knitted Fabrics Using Multi-criteria Decision-making Approach with Interval Data

2011 ◽  
Vol 6 (3) ◽  
pp. 155892501100600 ◽  
Author(s):  
Abdolrasool Moghassem ◽  
Alireza Fallahpour
Keyword(s):  
Decision Making ◽  
Interval Data ◽  
Quality Parameters ◽  
Multi Criteria Decision Making ◽  
Experimental Conditions ◽  
Knitted Fabrics ◽  
Weft Knitted Fabric ◽  
Spun Yarn ◽  
Relative Closeness ◽  
Rotor Spun Yarn

Selecting appropriate spinning conditions according to the properties of the final yarn is an intricate aspect and is inherently a multi-criteria decision-making (MCDM) problem. In recent years, various MCDM approaches have been used for solving such kind of the problems with exact value of the attributes. But, values of the properties for a yarn are affected by some factors such as specimen length, number of tests and experimental conditions. Therefore, decision-makers use average values instead of exact values for calculation. Considering existing difficulties in determining precisely the exact values of the attributes, their values can be considered as intervals. Therefore, in the present study, appropriate components of the doffing tube and its adjustment for rotor spun yarn intended to be used for weft knitted fabric were selected by extended version of the TOPSIS. Three important variables were considered and their performances were evaluated based on the seven quality parameters of the sixteen produced yarns. The final ranking was elicited in accordance with the relative closeness coefficient to the ideal solution and the best alternative which is able to increase weft knitting machine efficiency was presented. Consequently, stability of the proposed final ranking was verified after sensitivity analysis.

scholarly journals A Heterogeneous MCDM Framework for Sustainable Supplier Evaluation and Selection Based on the IVIF-TODIM Method

2019 ◽  
Vol 11 (18) ◽  
pp. 5057 ◽  
Author(s):  
Ren-Jie Mao ◽  
Jian-Xin You ◽  
Chun-Yan Duan ◽  
Lu-Ning Shao
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Third Party ◽  
Multi Criteria Decision Making ◽  
Interval Numbers ◽  
Intuitionistic Fuzzy Numbers ◽  
Sustainability Performance ◽  
Intuitionistic Fuzzy ◽  
Relative Closeness ◽  
Interval Valued

The third-party platform named ECO system is used by many transnational companies to monitor the sustainability performance of their global suppliers because of its easiness and shareability. Nonetheless, methods used in this platform for evaluating and calculating the sustainability performance of the alternative suppliers are criticized for their lack of accuracy. In response to these problems, this paper presents a heterogeneous multi-criteria decision-making (MCDM) method based on interval-valued intuitionistic fuzzy--an acronym in Portuguese for interactive multi-criteria decision making (IVIF--TODIM) to improve the efficiency of the evaluation model. Considering the varying features of evaluation criteria, i.e., either quantitative or qualitative, the evaluation values under different criteria are expressed in their appropriate information types. In this paper, a general method based on the relative closeness to the technique for order preference by similarity to ideal solution (TOPSIS) method is applied for aggregating the heterogeneous assessment information, including crisp numbers, interval numbers, and triangular fuzzy numbers (TFNs), into interval-valued intuitionistic fuzzy numbers (IVIFNs). Then, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) is extended and employed to prioritize the alternative suppliers. Finally, the applicability and effectiveness of the proposed method is verified by a practical example of polymer manufacturing company and a comparison analysis with existing methods.

Ranking Alternatives in Rotor-Spun Knitting Process Using Extended VIKOR on Interval Data

2014 ◽  
Vol 9 (4) ◽  
pp. 155892501400900
Author(s):  
Alireza Fallahpour ◽  
Ezutah Udoncy Olugu ◽  
Abdolrasool Moghassem ◽  
Siti Nurmaya Musa
Keyword(s):  
Interval Data ◽  
Quality Parameters ◽  
Ideal Solution ◽  
Extended Version ◽  
Engineering Applications ◽  
Yarn Properties ◽  
Relative Closeness ◽  
The Ideal

Assigning precise values for attributes in most engineering applications is almost impossible. It is therefore necessary to consider yarn properties as intervals. Hence, an extended version of VIKOR was employed in this study to select suitable spinning conditions for the weft knitting process among feasible alternatives. Three variables in rotor-spun box were considered and their performances were evaluated based on seven quality parameters using 16 yarn samples. The final ranking was presented according to the relative closeness coefficient of the ideal solution. Consequently, stability of the proposed final ranking was verified.

Multi-Criteria Decision Making Methods for Designing Optomechatronic Systems

2015 ◽  
Vol 220-221 ◽  
pp. 188-193
Author(s):  
Tomasz Giesko
Keyword(s):  
Decision Making ◽  
Vision System ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Relative Closeness ◽  
Innovative Solutions ◽  
Essential Problem ◽  
Economic Criteria ◽  
The Ideal

When designing unique optomechatronic systems with the application of innovative solutions, decision making with respect to a number of technical and economic criteria seems to be an essential problem. The multi-criteria decision theory is a process of selecting the best solution to the set of alternatives. The paper presents the application of the TOPSIS method for working towards a solution to decision making in the process of designing a unique measurement vision system. The set of alternatives for the vision system has been considered with regard to benefit and cost criteria. As a result, the best alternative has been identified, which represents the highest similarity to the ideal solution expressed by the value of the relative closeness index.

scholarly journals A Data Pre-Processing Model for the Topsis Method

2016 ◽  
Vol 16 (2) ◽  
pp. 219-235 ◽  
Author(s):  
Andrzej Kobryń ◽  
Joanna Prystrom
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Interval Data ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Real Numbers ◽  
Calculation Algorithms ◽  
Negative Ideal Solution ◽  
The Ideal

AbstractTOPSIS is one of the most popular methods of multi-criteria decision making (MCDM). Its fundamental role is the establishment of chosen alternatives ranking based on their distance from the ideal and negative-ideal solution. There are three primary versions of the TOPSIS method distinguished: classical, interval and fuzzy, where calculation algorithms are adjusted to the character of input rating decision-making alternatives (real numbers, interval data or fuzzy numbers). Various, specialist publications present descriptions on the use of particular versions of the TOPSIS method in the decision-making process, particularly popular is the fuzzy version. However, it should be noticed, that depending on the character of accepted criteria – rating of alternatives can have a heterogeneous character. The present paper suggests the means of proceeding in the situation when the set of criteria covers characteristic criteria for each of the mentioned versions of TOPSIS, as a result of which the rating of the alternatives is vague. The calculation procedure has been illustrated by an adequate numerical example.

scholarly journals Effect of Lowering Twist Levels on Quality Parameters of Rotor Spun Cotton Yarn

2016 ◽  
Vol 35 (3) ◽  
pp. 425-430
Author(s):  
Farooq Ahmed ◽  
Ghulam Yasin Shaikh ◽  
Ashfaq Ahmed Pathan
Keyword(s):  
Quality Parameters ◽  
Test Methods ◽  
Standard Test ◽  
Cotton Yarn ◽  
Mass Variation ◽  
Yarn Strength ◽  
Spun Yarn ◽  
Twist Level ◽  
Rotor Spun Yarn

Investigations were made to explore the influence of lowering twist level on quality characteristics of rotor spun yarn. Three levels of yarn linear density (i.e. 40, 35 and 30 tex) and five levels of twist (i.e. 700, 600, 550, 500, and 450) were employed during yarn spinning trials. Each twist multiple was investigated at all linear densities for tensile strength, elongation, total CVm (Coefficient of Mass Variation) imperfection index and hairiness. 100% cotton yarn samples were prepared on Reiter R-40 at rotor speed of 90,000 rpm. Determination of elongation, yarn strength, hairiness, mass variation, and total imperfections index was carried out on Uster Tensorapid-4 and Uster Tester-4 as per set standards of ISO standard test methods. Based on investigations it is established that yarn strength and elongation declined minutely (Insignificant) with lowering twist levels but still can be confidently used for knitting yarns. However, significant improvement in total imperfection index and marginal enhancement in CVm were experienced.

scholarly journals TOPSIS model based on entropy and similarity measure for market segment selection and evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Truong Thi Thuy Duong ◽  
Nguyen Xuan Thao
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Multi Criteria Decision Making ◽  
Market Segment ◽  
Content Type ◽  
Model Based ◽  
Relative Closeness ◽  
Decision Making Problem ◽  
Topsis Approach ◽  
Topsis Model

PurposeThe paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.Design/methodology/approachIntroducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.FindingsThe outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.Originality/valueThis paper put forward an effective multi-criteria decision-making dealing with uncertain information.

scholarly journals Formulation of a novel drinking water quality index equation with the application of multi-criteria decision making techniques

2021 ◽  
Author(s):  
Deepjyoti Deb ◽  
Tilottama Chakraborty ◽  
Mrinmoy Majumder
Keyword(s):  
Water Quality ◽  
Decision Making ◽  
Water Quality Index ◽  
Quality Index ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Level ◽  
Multi Criteria Decision Making ◽  
Weighted Arithmetic ◽  
Weighted Values

Abstract Water Quality Index elucidates the complexity in assessing water quality by converting the results of various parameters into a single number for a precise interpretation of the condition of concerning water. The present study focuses on implementing Multi-Criteria decision-making techniques, namely, Analytical Hierarchy Process and Analytical Networking Process, in estimating the relative weighted significance values of the water quality parameters based on three novel criteria like Cost, Potability, and Taste. The suggested Water Quality Index technique utilizes these weighted values of the water quality parameters in depicting and expressing the water quality level in the form of an index value. Dissolved Oxygen has emerged as the most persuasive factor in evaluating water quality for drinking purposes in this study. This paper has also suggested modifying the standard weighted arithmetic water quality index for higher accuracy in results. Furthermore, Sensitivity analysis is performed to corroborate the Multi-Criteria Decision Making approach in index assessment. The accuracy of the Water Quality Index analysis shall improve if a fixed set of criteria and their preference are asserted and justified based on which the water quality parameters are ranked. Their weighted significance values will be estimated accordingly.

MULTI-CRITERIA DECISION-MAKING METHOD BASED ON INDUCED INTUITIONISTIC NORMAL FUZZY RELATED AGGREGATION OPERATORS

2012 ◽  
Vol 20 (04) ◽  
pp. 559-578 ◽  
Author(s):  
JIAN-QIANG WANG ◽  
KANG-JIAN LI ◽  
HONG-YU ZHANG
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Score Function ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Multi Criteria Decision Making ◽  
Ordered Weighted Averaging ◽  
Averaging Operator ◽  
Relative Closeness ◽  
Ordered Weighted Averaging Operator

In this paper, we first defined intuitionistic normal fuzzy numbers as well as their operational laws and score function. Next, we proposed some aggregation operators including ordered intuitionistic normal ordered fuzzy weighted averaging operator, intuitionistic normal fuzzy ordered weighted geometric averaging operator, intuitionistic normal fuzzy related ordered weighted averaging operator, intuitionistic normal fuzzy related ordered weighted geometric averaging operator, induced intuitionistic normal fuzzy related ordered weighted averaging operator and induced intuitionistic normal fuzzy related ordered weighted geometric averaging operator. After that, similarity measure between two intuitionistic normal fuzzy numbers is defined. For multi-criteria decision making problems, in which the criteria are interactive and the criteria values are intuitionistic normal fuzzy numbers, an approach based on induced intuitionistic normal fuzzy related aggregation operators is proposed. And the comprehensive evaluation values of all alternatives can be derived by applying induced intuitionistic normal fuzzy related aggregation operators. Finally, the ranking of the whole alternatives set can be obtained by comparing the relative closeness of alternatives to the ideal solution. In the end, an example is given to show the validity and the feasibility of the method.

scholarly journals APPLICATION OF MULTI CRITERIA DECISION TECHNIQUE TO DETERMINE THE BEST CHICKPEA CULTIVARS WITH HIGH ANTIOXIDANT POTENTIAL

AGROFOR ◽  
2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Levent Yurdaer AYDEMİR ◽  
Sema AYDEMİR ◽  
Fatma Gizem AKÇAKAYA
Keyword(s):  
Decision Making ◽  
Radical Scavenging Activity ◽  
Radical Scavenging ◽  
Water Soluble ◽  
Total Phenolic ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Relative Closeness ◽  
Chickpea Cultivars

In this study, technique for order preference by similarity to ideal solution(TOPSIS) analysis, which is multi criteria decision making method, was firstlyapplied to rank the most suitable cultivars among 12 registered chickpeas for highantioxidant potentials. Registered chickpea cultivars were grown in trial fields ofstate research institute in 2015, Adana, Turkey. The cultivars were analyzed for thecriteria such as their water-soluble protein content (WSPC), total phenolic content(TPC), free radical scavenging activity (FRSA) and iron chelating activity (ICA)which were related to their antioxidant potentials. However, depending on eachcriterion, the ranking of the cultivars was completely different so that TOPSISanalysis was applied to the obtained data in six steps. Firstly, the decision matrixwas constructed and then each criterion was weighted as respectively 0.40, 0.30,0.20, 0.10 for FRSA, TPC, ICA, and WSPC by the researchers. After the weightednormalized decision matrix was constructed, the positive ideal and negative idealsolutions were determined. Then the separation measures for each alternative werecalculated (Si* and Si- for the separation from positive and negative idealalternative, respectively). Finally, the relative closeness to ideal solution wascalculated (Ci*). The cultivar Seçkin with the highest Ci* value (0.776) was thefirst rank and followed by Aydın, Azkan, and Çakır. This study showed theusefulness of TOPSIS analysis in the multi criteria decision making process whenthe presence of different parameters related to same property of sample set such asantioxidant potential of chickpea cultivars.

Some Score Functions on Fermatean Fuzzy Sets and Its Application to Bride Selection Based on TOPSIS Method

2021 ◽  
Vol 10 (3) ◽  
pp. 18-29
Author(s):  
Laxminarayan Sahoo
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Score Function ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Topsis Method ◽  
Score Functions ◽  
Relative Closeness ◽  
Separation Measure

The aim of this paper is to propose some score functions for the fruitful ranking of fermatean fuzzy sets (FFSs) and fermatean fuzzy TOPSIS method based on proposed score functions. fermatean fuzzy sets proposed by Senapati and Yager can handle uncertain information more easily in the process of multi-criteria decision making (MCDM). In this paper, the authors have proposed three newly improved score functions for effective ranking of fermatean fuzzy sets. Here, they have applied the proposed score function to calculate the separation measure of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficient. Based on different types of score functions, they have employed the TOPSIS method to solve the multi-criteria decision-making (MCDM) problem in which all preference information provided by the decision makers is expressed in terms of fermatean fuzzy decision matrices. Finally, a numerical example for selecting the bride form matrimonial site has been considered to illustrate the proposed method.

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