scholarly journals SUPPLIER SELECTION PROCESS IN DAIRY INDUSTRY USING FUZZY-TOPSIS METHOD

2021 ◽  
Vol 4 (1) ◽  
pp. 82-98
Author(s):  
Tarik Cakar ◽  
◽  
Burcu Çavuş ◽  
Keyword(s):  
Supplier Selection ◽  
Selection Criteria ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Fuzzy Environment ◽  
Quality Of Products ◽  
Topsis Technique ◽  
The Right

Supplier selection is one of the most critical processes within the purchasing function. Choosing the right supplier makes a strategic difference to an organization’s ability to reduce costs and improve the quality of products by helping to select the most suitable supplier. Sütaş Dairy Company, which is entered to Macedonia market in 2012. In the dairy company, there is only one purchasing manager who selects the farmers. Importance weights of criteria are determined using his reference, and also the alternatives are evaluated according to each criterion. The most important criteria are product and other costs, the price is also playing an important role, but due to the small marketplace of Macedonia, the prices are almost the same in every region. To select the dairy supplier in Macedonia, Fuzzy-TOPSIS technique is used. The main goal of using fuzzy logic in this study is to help decision-makers for identifying the importance of selection criteria and rank possible suppliers easily. Since the supplier selection process is a Multi-Criteria Decision Making (MCDM) problem, after identify the weights and rankings in a fuzzy environment, TOPSIS algorithm has been used in the rest of the problem. Finally, fuzzy TOPSIS methodology has been implemented successfully, and its result pointed out the most suitable suppliers.

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

A Multicriteria Multilevel Group Decision Method for Supplier Selection and Order Allocation

2012 ◽  
Vol 3 (1) ◽  
pp. 81-105 ◽  
Author(s):  
Mariya A. Sodenkamp ◽  
Leena Suhl
Keyword(s):  
Supplier Selection ◽  
Group Decision ◽  
Selection Process ◽  
Large Body ◽  
Decision Makers ◽  
Order Allocation ◽  
Decision Factors ◽  
Selection Decisions ◽  
Allocation Decisions

Supplier selection is an integral part of supply chain management (SCM). It plays a prominent role in the purchasing activity of manufacturing and trading companies. Evaluation of vendors and procurement planning requires simultaneous consideration of tangible and intangible decision factors, some of which may conflict. A large body of analytical and intuitive methods has been proposed to trade off conflicting aspects of realism and optimize the selection process. In the large companies the fields of decision makers’ (DMs) expertise are highly distributed and DMs’ authorities are unequal. On the other hand, the decision components and their interactions are very complex. These facts restrict the effectiveness of using the existing methods in practice. The authors present a multicriteria decision analysis (MCDA) method which facilitates making supplier selection decisions by the distributed groups of experts and improves quality of the order allocation decisions. A numerical example is presented and applicability of the proposed algorithm is demonstrated in the Raiffeisen Westfalen Mitte, eG in Germany.

scholarly journals MULTI-CRITERIA DECISION APPROACH WITH AHP AND IF-TOPSIS METHODS FOR R&D PROJECT SELECTION PROCESS

2019 ◽  
Vol 25 (3) ◽  
pp. 22-32
Author(s):  
EZGİ GÜLER ◽  
SELEN AVCI ◽  
ZERRİN ALADAĞ
Keyword(s):  
Selection Process ◽  
Fuzzy Topsis ◽  
Project Selection ◽  
Decision Makers ◽  
Topsis Method ◽  
Analytic Hierarchy ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Intuitionistic Fuzzy Topsis ◽  
Hierarchy Process

In this study, we examined the project selection process in a mould manufacturing company. We ranked 12 criteria via Analytic Hierarchy Process (AHP) and evaluated the most important 8 criteria. Then we applied Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) method, which is the extended version of the TOPSIS method in intuitionistic fuzzy environment. After expressing the decision makers' evaluations in linguistic terms, we turned them into intuitive fuzzy numbers. In the last step, we obtained the project rankings by calculating the closeness coefficient for 5 projects.

Design of Supplier Selection Procedure in Garment Company

2014 ◽  
Vol 606 ◽  
pp. 241-245
Author(s):  
Reni Amaranti ◽  
Agus N. Supena ◽  
Agelin S. Ramadhani
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Business Processes ◽  
Raw Materials ◽  
Selection Process ◽  
Selection Procedure ◽  
Purchasing Department ◽  
Quality Of Products ◽  
Hierarchy Process

The purchase of raw materials is very influential for the quality of products produced in addition to the process of making the product itself. Therefore, how to choose the supplier from the available alternatives is something that must be done properly in the process of procurement of raw materials especially for companies with many product variations and associated with many suppliers. This paper discusses about how to make supplier selection procedure for garment company with a case on a medium scale garment company in Bandung that manufactures veil and Moslem fashion. Mapping of business processes using IDEF0 was the first step in designing of supplier selection procedure. Then performed an analysis of the process which is usually done to identify the weaknesses and strengths of the process. The next step is create a design of supplier selection procedure that is more structured and measurable. In addition, also designed a tool that can be used in the supplier selection process, which is a simple application to determine the ranking of suppliers who will be selected based on the criteria specified. The application is based on the decision-making process with The Analytical Hierarchy Process approach that has been commonly used as a tool for decision-making with many alternative choices. In general, the resulting procedure would be beneficial for the company as a guide for those involved in the procurement process at the purchasing department, primarily for decision making in supplier selection.

An Integrated Fuzzy Multi-Attribute Decision-Making Methodology for Evaluation of Mechanical Product

2010 ◽  
Vol 450 ◽  
pp. 534-538
Author(s):  
Yuan Chen ◽  
Bing Li ◽  
Xiao Jun Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Weighting Method ◽  
Fuzzy Environment ◽  
Design Alternatives ◽  
Concept Evaluation ◽  
Criteria Weights ◽  
Multi Attribute Decision Making ◽  
Topsis Technique

The concept evaluation of mechanical product is essentially a multi-attribute decision making (MADM) problem in the fuzzy environment. In order to reduce the adverse impact of preference or judgments of decision makers on the final evaluation results, this paper attempts to propose an integrated fuzzy multi-attribute decision making methodology that combines the fuzzy TOPSIS technique and the objective weighting to evaluate mechanical product. The fuzzy TOPSIS technique is applied to rank the design alternatives, and the objective weighting method is integrated into the fuzzy TOPSIS technique to determine the appropriate criteria weights. Finally, a real application to pan mechanism selection for a cooking robot is demonstrated.

scholarly journals Supplier Selection and Performance Evaluation for High-Voltage Power Film Capacitors in a Fuzzy Environment

2019 ◽  
Vol 9 (23) ◽  
pp. 5253 ◽  
Author(s):  
Chun-Ming Yang ◽  
Kuen-Suan Chen ◽  
Ting-Hsin Hsu ◽  
Chang-Hsien Hsu
Keyword(s):  
High Voltage ◽  
Supplier Selection ◽  
Selection Process ◽  
High Reliability ◽  
Decision Makers ◽  
Electrical Performance ◽  
Cognitive Differences ◽  
Inference System ◽  
Supplier Performance

Rapid advances in technology have shortened the upgrade and replacement cycles in industries such as electronics, household appliances, and communication technologies. Within these industries, high-voltage power film capacitors have become indispensable electrical components due to their good electrical performance and high reliability. The selection and evaluation of suppliers of these capacitors is therefore increasingly important. Suppliers play a crucial role in the electronics industry; the quality of their products determines the degree to which the quality of the final product can be guaranteed. Supplier quality also affects the ability of all the members in a supply chain to control costs. Evaluation by decision-makers is highly significant in the supplier selection process. However, when the opinions of multiple decision-makers are combined, issues such as cognitive differences, fuzzy linguistics, and uncertainty are common. This study presents a supplier performance index SPL and derives the estimates of the index SPL and its statistical properties. The proposed index is not only helpful for the accurate measurement of supplier performance; it can also reduce cognitive differences among evaluators in the decision-making process (that is, the sample variability associated with the Likert scale). Evaluation scores for each criterion for the linguistic labels are converted to triangular fuzzy numbers in order to reduce ambiguity. Subsequently, integrated crisp values are obtained by defuzzification in a fuzzy inference system. A real-world case study of the supplier selection of high-voltage power film capacitors is provided to illustrate the efficacy of the proposed method.

scholarly journals Supplier Selection with Fuzzy TOPSIS and VIKOR Method in a Trailer Manufacturing Company

2018 ◽  
Vol 1 (1) ◽  
pp. 1100-1109
Author(s):  
Seher Arslankaya
Keyword(s):  
Supplier Selection ◽  
High Speed ◽  
Lower Cost ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Strategic Decision ◽  
Profit Margins ◽  
Production And Distribution ◽  
Selection Decision ◽  
The Right

The supplier decision has become a strategic decision for companies to achieve competitive advantage due to growth and increased competition, technology and reduced profit margins. The right choice of the supplier is one of the most important elements that will ensure the production and distribution of the products with the desired quality, flexibility, lower cost and high speed. There may be complexity and uncertainty in supplier selection decision as it includes many factors and multiple decision makers. For this purpose, the right supplier to be cooperated has been decided by using fuzzy TOPSIS and VIKOR methods in Microsoft Visual Basic by evaluating existing suppliers in a trailer factory operating in Turkey.

scholarly journals MULTI-CRITERIA DECISION APPROACH WITH AHP AND IF-TOPSIS METHODS FOR R&D PROJECT SELECTION PROCESS

2019 ◽  
Vol 25 (3) ◽  
Author(s):  
EZGİ GÜLER ◽  
SELEN AVCI ◽  
ZERRİN ALADAĞ
Keyword(s):  
Selection Process ◽  
Fuzzy Topsis ◽  
Project Selection ◽  
Decision Makers ◽  
Topsis Method ◽  
Analytic Hierarchy ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Intuitionistic Fuzzy Topsis ◽  
Hierarchy Process

In this study, we examined the project selection process in a mould manufacturing company. We ranked 12 criteria via Analytic Hierarchy Process (AHP) and evaluated the most important 8 criteria. Then we applied Intuitionistic Fuzzy TOPSIS<strong> (</strong>IF-TOPSIS) method, which is the extended version of the TOPSIS method in intuitionistic fuzzy environment. After expressing the decision makers' evaluations in linguistic terms, we turned them into intuitive fuzzy numbers. In the last step, we obtained the project rankings by calculating the closeness coefficient for 5 projects

scholarly journals Comparative Analysis of Hybrid Fuzzy MCGDM Methodologies for Optimal Robot Selection Process

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 839
Author(s):  
Tabasam Rashid ◽  
Asif Ali ◽  
Juan Guirao ◽  
Adrián Valverde
Keyword(s):  
Selection Process ◽  
Industrial Robot ◽  
Vital Role ◽  
Decision Makers ◽  
Fuzzy Information ◽  
Criteria Weights ◽  
Topsis Technique ◽  
Fuzzy Weights ◽  
Robot Selection ◽  
Interval Valued

The generalized interval-valued trapezoidal fuzzy best-worst method (GITrF-BWM) provides more reliable and more consistent criteria weights for multiple criteria group decision making (MCGDM) problems. In this study, GITrF-BWM is integrated with the extended TOPSIS (technique for order preference by similarity to the ideal solution) and extended VIKOR (visekriterijumska optimizacija i kompromisno resenje) methods for the selection of the optimal industrial robot using fuzzy information. For a criteria-based selection process, assigning weights play a vital role and significantly affect the decision. Assigning weights based on direct opinions of decision makers can be biased, so weight deriving models, such as GITrF-BWM, overcome this discrepancy. In previous studies, generalized interval-valued trapezoidal fuzzy weights were not derived by using any MCGDM method for the robot selection process. For this study, both subjective and objective criteria are considered. The preferences of decision makers are provided with the help of linguistic terms that are then converted into fuzzy information. The stability and reliability of the methods were tested by performing sensitivity analysis, which showed that the ranking results of both the methodologies are not symmetrical, and the integration of GITrF-BWM with the extended TOPSIS method provides stable and reliable results as compared to the integration of GITrF-BWM with the extended VIKOR method. Hence, the proposed methodology provides robust optimal industrial robot selection.

A TODIM-Based Decision Support Framework for G-Resilient Supplier Selection in Fuzzy Environment

2016 ◽  
Vol 33 (05) ◽  
pp. 1650033 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Support ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Selection Problems ◽  
Fuzzy Environment ◽  
Decision Support Framework ◽  
Application Potential

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. In this work subjectivity of evaluation criteria has been tackled by exploring fuzzy set theory. A dominance based approach has been conceptualized which is basically a simplified version of TODIM. Application potential of the proposed dominance based fuzzy decision making approach has been compared to that of fuzzy-TOPSIS, fuzzy-VIKOR and also fuzzy-TODIM. The concept of a unique performance index, i.e. “g-resilient” index has been introduced here to help in assessing suppliers’ performance and thereby selecting the best candidate. The work has also been extended to identify the areas in which suppliers are lagging; these seek further improvement towards g-resilient suppliers’ performance to be boosted up to the desired level.

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