scholarly journals Selection of an Inert Gas System for the Transportation of Direct Reduced Iron

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Devran Yazir ◽  
Bekir Sahin ◽  
Murat Alkac
Keyword(s):  
Fuzzy Topsis ◽  
Inert Gas ◽  
Decision Making Process ◽  
Shipping Industry ◽  
Topsis Method ◽  
Direct Reduced Iron ◽  
Gas System ◽  
Production Stages ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Direct reduced iron (DRI) can create significant risks such as ignition, explosion, and fire because of the oxidation reaction in case when DRI undergoes spontaneously heating and comes in contact with oxygen or water. For this reason, the transportation of DRI is classified as a dangerous task of which the inert process should be done in the ship’s holds. Many studies have been conducted on the production and production stages of DRI and other areas of use of inert gas, but no studies have been conducted on the safe transportation of this cargo by ships. This study analyzes the criteria and alternatives for selecting the inert gas system for the benefits of investors and shipowners in the shipping industry. The intuitionistic fuzzy TOPSIS (IF-TOPSIS) method is implemented to conduct the decision-making process. As a result of this study, preferences for candidate inert gas systems are modelled. Port facility nitrogen generator is selected as the most suitable inert gas system among alternative inert gas systems based on predetermined criteria.

A decision making model for selecting start-up businesses in a government venture capital scheme

2016 ◽  
Vol 54 (3) ◽  
Author(s):  
Eric Afful-Dadzie ◽  
Anthony Afful-Dadzie
Keyword(s):  
Decision Making ◽  
Venture Capital ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Start Up ◽  
Start Ups ◽  
Intuitionistic Fuzzy Topsis ◽  
Practical Implications ◽  
Selection Of

Purpose The paper proposes an intuitionistic fuzzy TOPSIS multi-criteria decision making (MCDM) method for the selection of start-up businesses in a government venture capital (GVC) scheme. Most GVC funded start-ups fail or underperform compared to those funded by private venture capitals due to a number of reasons including lack of transparency and unfairness in the selection process. By its design, the proposed method is able to increase transparency and reduce the influence of bias in GVC start-up selection processes. The proposed method also models uncertainty in the selection criteria using fuzzy set theory that mirrors the natural human decision making process. Design/methodology/approach The proposed method first presents a set of criteria relevant to the selection of early stage but high potential start-ups in a Government Venture Capital (GVC) financing scheme. These criteria are then analyzed using the TOPSIS method in an intuitionistic fuzzy environment. The intuitionistic Fuzzy Weighted Averaging (IFWA) Operator is used to aggregate ratings of decision makers. A numerical example of how the proposed method could be used in GVC start-up candidates’ selection in a highly competitive government venture capital scheme is provided. Findings The methodology adopted increases fairness and transparency in the selection of start-up businesses for fund support in a government-run venture capital scheme. The criteria set proposed is ideal for selecting start-up businesses in a government controlled venture capital scheme. The decision making framework demonstrates how uncertainty in the selection criteria are efficiently modelled with the TOPSIS method. Practical implications As government venture capital schemes increase around the world, and concerns about failure and underperformance of GVC funded start-ups increase, the proposed method could help bring formalism and ensure the selection of start-ups with high success potential. Originality/value The framework designs relevant sets of criteria for a selection problem, demonstrates the use of extended TOPSIS method in intuitionistic fuzzy sets and apply the proposed method in an area that has not been considered before. Additionally, it demonstrates how intuitionistic fuzzy TOPSIS could be carried out in a real decision making application setting.

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.

Note on the Application of Intuitionistic Fuzzy TOPSIS Model for Dealing With Dependent Attributes

2019 ◽  
Vol 6 (2) ◽  
pp. 20-32
Author(s):  
Daniel Osezua Aikhuele
Keyword(s):  
State Of The Art ◽  
Fuzzy Topsis ◽  
The State ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Normalization Methods ◽  
The One ◽  
Intuitionistic Fuzzy Topsis ◽  
Topsis Model

In this article, the effectiveness of the intuitionistic fuzzy TOPSIS model (IF-TOPSISEF) is tested for addressing, capturing, and resolving the effect of correlation between attributes, otherwise called the dependency of attributes. This was achieved by using several normalization methods in the implementation of the IF-TOPSISEF model. Furthermore, the result of the computation is compared with the one obtained when the normalization methods are implemented using a traditional TOPSIS model. The study contributes and extends the state of the art in TOPSIS method study, by addressing, capturing and resolving the effect of correlation between attributes otherwise called dependency of attributes.

scholarly journals Application of TOPSIS in the Diagnosis of Vector Borne Diseases

2019 ◽  
Vol 8 (6) ◽  
pp. 5217-5223
Keyword(s):  
Current Model ◽  
Intuitionistic Fuzzy Set ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Entropy Weight ◽  
Vector Borne Diseases ◽  
Intuitionistic Fuzzy ◽  
Vector Borne ◽  
Specific Symptoms ◽  
Intuitionistic Fuzzy Topsis

“Intuitionistic Fuzzy Set” (IFS) is used to manage nebulousness and indecision. In current investigation, another intuitionistic fuzzy TOPSIS method is proposed for decision making by utilizing entropy weight. Current model permits estimating the degree of membership and non-membership of various alternatives assessed over a criterion set. A case study has been carried out to diagnosis of vector borne disease. Criteria’s have been selected according to relevant disease and weight has been assigned to them by medical expert’s committee. It has been established that TOPSIS method can diagnose the VBD diseases using specific symptoms as criteria and VBDs as alternatives. The suggested methodology can help in correct and timely diagnosis of VBDs and provides doctors an innovative diagnostic tool (WHO, 2004; WHO, 2014). The result is validated by applying fuzzy VIKOR method.

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.

scholarly journals A TWO PHASED FUZZY METHODOLOGY FOR SELECTION AMONG MUNICIPAL PROJECTS

2015 ◽  
Vol 21 (3) ◽  
pp. 405-422 ◽  
Author(s):  
Mehmet Emin BAYSAL ◽  
İhsan KAYA ◽  
Cengiz KAHRAMAN ◽  
Ahmet SARUCAN ◽  
Orhan ENGIN
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Community Life ◽  
Topsis Method ◽  
Complex Processes ◽  
Central District ◽  
Selection Of

A municipality improves the quality of community life through its projects and actions. However, project selection and prioritization by municipalities are highly complex processes. Therefore, multicriteria decision making (MCDM) methodologies are very suitable for determining the best alternative. Recently, some studies have concentrated on the selection of the best project alternatives. In this paper, a two phased fuzzy MCDM methodology is proposed for the selection among municipal projects. In the first phase, fuzzy TOPSIS method is used to select the main project group and then fuzzy AHP is used to select the best sub-municipal project. The application of the suggested methodology has been made at the central district municipality in Konya, Turkey.

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