scholarly journals A Novel Coordinated TOPSIS Based on Coefficient of Variation

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 614 ◽  
Author(s):  
Pengyu Chen
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Coefficient Of Variation ◽  
Ideal Solution ◽  
Comparison Results ◽  
Order Preference ◽  
Modified Topsis ◽  
Coordination Degree

Coordinated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a significant improvement of TOPSIS, which take into account the coordination level of attributes in the decision-making or assessment. However, in this study, it is found that the existing coordinated TOPSIS has some limitations and problems, which are listed as follows. (1) It is based on modified TOPSIS, not the original TOPSIS. (2) It is inapplicable when using vector normalization. (3) The calculation formulas of the coordination degree are incorrect. (4) The coordination level of attributes is interrelated with the weights. In this paper, the problems of the existing coordinated TOPSIS are explained and revised, and a novel coordinated TOPSIS based on coefficient of variation is proposed to avoid the limitations. Comparisons of the existing, revised, and proposed coordinated TOPSIS are carried out based on two case studies. The comparison results validate the feasibility of the proposed coordinated TOPSIS.

scholarly journals Fluid Selection of Organic Rankine Cycle Using Decision Making Approach

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Aditya Chauhan ◽  
Rahul Vaish
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Correlation Coefficient ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Power Production ◽  
Ideal Solution ◽  
Topsis Method ◽  
Order Preference ◽  
Selection Of

An attempt has been made to rank and classify potential fluids for power production through organic rankine cycle (ORC) using technique for order preference by similarity to ideal solution (TOPSIS) method. In order to calculate subjective weights for the attributes under study, the modified digital logic (MDL) method has been used. It has been observed under two different case studies that R601 (pentane) shows promising results. These fluids are further classified using dendrogram, a hierarchical clustering technique. Finally Pearson's correlation coefficient is calculated for the attributes to find out the nature and degree of correlation between different attributes under study.

scholarly journals A Comparative Study on Decision Making Methods with Interval Data

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Aditya Chauhan ◽  
Rahul Vaish
Keyword(s):  
Decision Making ◽  
Input Data ◽  
Multiple Criteria Decision Making ◽  
Interval Data ◽  
Cross Entropy ◽  
Ideal Solution ◽  
Order Preference ◽  
Topsis Technique ◽  
Selection Of ◽  
Novel Algorithm

Multiple Criteria Decision Making (MCDM) models are used to solve a number of decision making problems universally. Most of these methods require the use of integers as input data. However, there are problems which have indeterminate values or data intervals which need to be analysed. In order to solve problems with interval data, many methods have been reported. Through this study an attempt has been made to compare and analyse the popular decision making tools for interval data problems. Namely, I-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), DI-TOPSIS, cross entropy, and interval VIKOR (VlseKriterijumska Optimiza-cija I Kompromisno Resenje) have been compared and a novel algorithm has been proposed. The new algorithm makes use of basic TOPSIS technique to overcome the limitations of known methods. To compare the effectiveness of the various methods, an example problem has been used where selection of best material family for the capacitor application has to be made. It was observed that the proposed algorithm is able to overcome the known limitations of the previous techniques. Thus, it can be easily and efficiently applied to various decision making problems with interval data.

scholarly journals A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Ease Of Use ◽  
Decision Makers ◽  
Ideal Solution ◽  
Interval Numbers ◽  
Group Matrix ◽  
Order Preference ◽  
Criteria Weights

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.

scholarly journals Comparison of the Economic Performance of Turkish Republics in Central Asia with TOPSIS Method

2015 ◽  
Author(s):  
Ziya Gökalp Göktolga ◽  
Engin Karakış ◽  
Hakan Türkay
Keyword(s):  
Decision Making ◽  
Central Asia ◽  
Economic Performance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Economic Management ◽  
Macroeconomic Indicators ◽  
Order Preference ◽  
Negative Ideal Solution

The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.

scholarly journals MODEL PENGAMBILAN KEPUTUSAN PENERIMA BANTUAN RASKIN MENGUNAKAN METODE WEIGHTED PRODUCT (WP) DAN TOPSIS

2019 ◽  
Vol 7 (2) ◽  
pp. 19-30
Author(s):  
Rustam Rustam ◽  
Dr Rz.Abdul Aziz
Keyword(s):  
Decision Making ◽  
Ideal Solution ◽  
Order Preference

Penelitian ini bertujuan untuk mengetahui langkah-langkah ataupun model  metode WP dan metode Topsis, serta membandingkan hasil analisis kedua metode tersebut, terkait pengambilan keputusan untuk menentukan penerima raskin di kecamatan way pengubuan lampung tengah. Penyerapan tenaga kerja yang rendah serta kemampuan sumber daya manusia yang kurang memadai membuat kehidupan masyarakat dibawah garis kemiskinan. Usaha pemerintah dengan meluncurkan berbagai jenis bantuan tidak membuat tingkat kemiskinan berkurang. Beberapa faktor penyebabnya antara lain pemberian bantuan tidak tepat sasaran dan kriteria yang digunakan sebagai dasar penilaian belum maximal. Pemilihan metode harus sesuai untuk mengantisipasi kesalahan terhadap data yang akan digunakan. Metode Weighted Product (WP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) bagian dari Multi-Attribut Decision Making (MADM) digunakan untuk melakukan perangkingan terhadap keseluruhan alternatif dari kriteria dan subkriteria yang telah ditentukan. Implementasi kedua metoda terhadap kesepuluh alternatif (Kecamatan way pengubuan lampung tengah) ternyata memberikan hasil yang sangat baik mengunakan dua metode ini. Dan hasil perhitungan kedua metode ini berbeda maka disimpulkan hasil terkecillah yang terbaik adalah  Topsis  dengan nilai: 0,070137683

scholarly journals A fuzzy multi-criteria decision-making method for purchasing life insurance in India

2021 ◽  
Vol 10 (1) ◽  
pp. 344-356
Author(s):  
Chinmaya Ranjan Pattnaik ◽  
Sachi Nandan Mohanty ◽  
Sarita Mohanty ◽  
Jyotir Moy Chatterjee ◽  
Biswajit Jana ◽  
...  
Keyword(s):  
Decision Making ◽  
Life Insurance ◽  
Complex Problem ◽  
Insurance Companies ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Insurance Company ◽  
Proposed Model ◽  
Decision Making Problem ◽  
Order Preference

Life insurance is an agreement between an insured and an insurer, where the insurer pays out a sum of money either on a specific period or the death of the insured. Now a day, People can buy a policy through an online platform. There are a lot of insurance companies available in the market, and each company has various policies. Selecting the best insurance company for purchasing an online term plan is a very complex problem. People may confuse to choose the best insurance company for buying an online term. It is a multi-criteria decision making (MCDM) problem, and the problem consists of different criteria and various alternatives. Here in this paper, a model has been proposed to solve this decision-making problem. In this model, a fuzzy multi-criteria decision-making approach combined with technique for order preference by similarity to ideal solution (TOPSIS) and it has been applied to rank the different insurance companies based on online term plans. The experimental results show that the life insurance corporation of India (LIC) gets the top rank out of 12 companies for purchasing an online term plan. A sensitivity analysis has been performed to validate the proposed model.

scholarly journals A Decision-Making Model of Technological-Focused Government Agency Selection of Technological Start-Up Businesses

2022 ◽  
Vol 19 (1) ◽  
pp. 1749
Author(s):  
Amnard Taweesangrungroj ◽  
Roongkiat Rattanabanchuen ◽  
Sukree Sinthupinyo
Keyword(s):  
Decision Making ◽  
Private Equity ◽  
Multiple Criteria Decision Making ◽  
Government Agencies ◽  
Ideal Solution ◽  
Start Up ◽  
Order Preference ◽  
Fuzzy Mcdm ◽  
Decision Making Framework ◽  
The Government

In developing countries, the government has played an important role in supporting startup businesses in various aspects, primarily through tech-focused government agencies. With a limited budget, the government agencies are critical to select plenty of tech startups for funding, leaving only promising tech startups. Consequently, government agencies inevitably face decision-making problems under uncertain circumstances, like private equity investment situations. Reviewing the relevant decision-making frameworks has identified that a classical multiple criteria decision-making (MCDM) approach is currently used, assuming decision-makers acquire complete information that is not realistic. Moreover, both qualitative and quantitative criteria used in evaluating startup businesses cannot represent the uncertainty which is the fundamental nature of the decision-making circumstance. Thus, this article presents a decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Besides, it identifies selection criteria with mixed research methodologies and determines weights of importance criteria by the Delphi method. Finally, the proposed framework results are fairness, transparency, and eliminating bias in decision-making, including more efficiency when the framework’s ranking orders significantly correspond with actual performances. HIGHLIGHTS Criteria for selecting start-up businesses in technological-focused government agencies A decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) The performance of the decision-making framework in selecting startup businesses to acquire high potential tech startups to drive the national economy GRAPHICAL ABSTRACT

Sign in / Sign up

Export Citation Format

Share Document