Developing MCDM Approach Based on GRA and TOPSIS

2010 ◽  
Vol 34-35 ◽  
pp. 1931-1935 ◽  
Author(s):  
Qi Bing Wang ◽  
An Hua Peng
Keyword(s):  
Decision Making ◽  
Comprehensive Evaluation ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Comprehensive Evaluation ◽  
Multiple Criteria ◽  
Shape Similarity ◽  
Ideal Solution ◽  
Relational Analysis ◽  
Order Preference ◽  
Grey Relational

Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.

scholarly journals Sistem Pendukung Keputusan Untuk Seleksi Penerimaan Dan Penentuan Posisi Karyawan

2016 ◽  
Vol 10 (1) ◽  
pp. 62
Author(s):  
Devi Martha Ariyanti ◽  
Fahrul Agus ◽  
Dyna Marisa Khairina
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Ideal Solution ◽  
Order Preference

Sumber Daya Manusia (SDM) merupakan sumber daya yang paling penting bagi organisasi. Salah satu proses yang paling penting bagi perusahaan adalah proses rekrutmen dan seleksi sumber daya manusia. Pada kenyataannya pengambilan keputusan secara efisien dan efektif pada saat melakukan seleksi terhadap sumber daya manusia bukanlah hal yang mudah, maka diperlukan suatu Sistem Pendukung Keputusan (SPK) untuk membantu memecahkan masalah tersebut. Dalam hal ini Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) dan Fuzzy Multiple Criteria Decision Making (FMCDM) digunakan sebagai metode untuk memberikan penilaian calon karyawan yang akan diseleksi. Dari beberapa data yang diujikan terhadap aplikasi ini menunjukkan bahwa calon karyawan ideal terhadap suatu posisi bukan hanya memiliki nilai kedekatan pada kriteria ideal yang diinginkan oleh perusahaan, tapi juga memiliki nilai dengan rentang menjauhi kriteria ideal yang tidak diinginkan oleh perusahaan.

scholarly journals Penentuan Wali Kelas Yang Ideal Menggunakan Metode TOPSIS

2019 ◽  
Vol 5 (2) ◽  
pp. 85
Author(s):  
Nafis Sururi ◽  
Kusrini Kusrini ◽  
Sudarmawan Sudarmawan
Keyword(s):  
Decision Making ◽  
School Environment ◽  
Formal Education ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Ideal Solution ◽  
Topsis Method ◽  
Order Preference ◽  
The Ideal

Pendidikan merupakan salah satu hal yang penting dalam suatu negara. Pendidikan bisa didapatkan pendidikan formal, informal maupun nonformal. Contoh pendidikan formal adalah sekolah dan pergururan tinggi, di dalam sekolahan terdapat wali kelas yang bertanggung jawab terhadap peserta didik di satu kelas atau ruang belajar di lingkungan sekolah. Dalam menentukan wali kelas yang ideal kepala sekolah dapat melihat karakteristik dan kemampuan yang dimiliki guru secara objektif. Multiple Criteria Decision Making (MCDM) merupakan salah satu metode yang paling banyak digunakan dalam pengambilan keputusan. Salah satu metode MCDM adalah Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Penelitian ini menggunakan metode TOPSIS yang dapat menganalisis keputusan multi-kriteria dimana metode tersebut dapat memilih alternatif terbaik dengan jarak terdekat dari alternatif ideal. Hasil yang diperoleh dari penelitian ini adalah Penentuan wali kelas dilakukan dengan cara mencari nilai preferensi setiap guru yang paling besar dari 3 kelas yang digunakan. Perhitungan yang dilakukan menggunakan bobot berbeda pada setiap kelas agar mendapatkan nilai prefensi sebagai acuan penentuan wali kelas yang ideal.Kata Kunci—Wali kelas, Ideal, TOPSISEducation is one of the important things in a country. Education can be obtained from formal, informal or non-formal education. Examples of formal education are schools and high schools, in schools there is a homeroom teacher who is responsible for students in one class or study room in a school environment. In determining the ideal homeroom, the principal can see the characteristics and abilities of the teacher objectively. Multiple Criteria Decision Making (MCDM) is one of the most widely used methods in decision making. One of the MCDM methods is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This study uses the TOPSIS method which can analyze multi-criteria decisions where the method can choose the best alternative with the closest distance from the ideal alternative. The results obtained from this study are Determination of the homeroom teacher is done by finding the preference value of each teacher, the largest of the 3 classes used. Calculations performed using different weights for each class in order to get the value of the prefix as a reference for determining the ideal homeroom teacher.Keywords—Homeroom teacher, Ideal, TOPSIS

MULTIPLE CRITERIA CONSTRUCTION MANAGEMENT DECISIONS CONSIDERING RELATIONS BETWEEN CRITERIA / DAUGIATIKSLIAI STATYBOS VALDYMO SPRENDIMAI ATSIŽVELGIANT Į RODIKLIŲ TARPUSAVIO PRIKLAUSOMYBĘ

2010 ◽  
Vol 16 (1) ◽  
pp. 109-125 ◽  
Author(s):  
Jurgita Antuchevičienė ◽  
Edmundas Kazimieras Zavadskas ◽  
Algimantas Zakarevičius
Keyword(s):  
Decision Making ◽  
Mahalanobis Distance ◽  
Construction Management ◽  
Distance Measure ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Ideal Solution ◽  
Order Preference ◽  
Topsis Technique

Decision making in construction management has been always complicated especially if there were more than one criterion under consideration. Multiple criteria decision making (MCDM) has been often applied for complex decisions in construction when a lot of criteria were involved. Traditional MCDM methods, however, operate with independent and conflicting criteria. While in every day problems a decision maker often faces interactive and interrelated criteria. Accordingly, the need of improving and supplementing the methodology of compromise decisions arose. It was proposed to supplement TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) method and integrate the Mahalanobis distance in the usual algorythm of TOPSIS. Mahalanobis distance measure offered an option to take the correlations between the criteria into considerations while making the decision. A case study of building redevelopment in Lithuanian rural areas was presented that demonstrated the application of the proposed methodology. The case study proved that the proposed TOPSIS‐M (TOPSIS applying Mahalanobis distance measure) method could have substantial influence in carrying the proper decision. Santrauka Statybos valdymo spendimų priėmimas visuomet yra komplikuotas, ypač jei turime atsižvelgti į daugelį rodiklių. Kompleksiniams statybos sprendimams, kurie apibūdinami daugeliu rodiklių, taikomi daugiatiksliai sprendimų priėmimo metodai (MCDM ‐ Multiple Criteria Decision Making). Šie metodai skirti sprendimams priimti tuomet, kai vertinami konfliktuojantys bei nepriklausomi rodikliai. Tačiau realiose situacijose, priešingai, nuolat susiduriame su saveikaujančiais ir tarpusavio priklausomybę turinčiais rodikliais. Dėl šios priežasties kyla poreikis patobulinti sprendimų metodologiją. Straipsnyje siūloma papildyti variantų racionalumo nustatymo metoda TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution), taikant Mahalanobio metoda atstumams nustatyti. Mahalanobio atstumų nustatymo metodas suteikia galimybę įvertinti koreliacinės rodiklių priklausomybės priimant daugiatikslį sprendimą. Siūlomos metodologijos taikymas įliustruojamas sprendžiant apleistų pastatų Lietuvos kaimo vietovėse racionalaus sutvarkymo uždavinį. Pateiktas pavyzdys patvirtina, kad TOPSIS‐M metodo (t. y. TOPSIS naudojant Mahalanobio atstuma) taikymas gali turėti esminę įtaka priimant sprendimą.

A method for threshold selection in load extrapolation based on multiple criteria decision-making technology

2017 ◽  
Vol 08 (03) ◽  
pp. 1750019
Author(s):  
Jixin Wang ◽  
Qingsong Liu ◽  
Xinting Zhai
Keyword(s):  
Decision Making ◽  
Comprehensive Evaluation ◽  
Multiple Criteria Decision Making ◽  
Entropy Method ◽  
Multiple Criteria ◽  
Threshold Selection ◽  
Selection Methods ◽  
Additional Method ◽  
Random Simulation ◽  
Peak Over Threshold

In order to establish an accurate peak over threshold (POT) model for reasonable load extrapolation, a new threshold selection method based on multiple criteria decision making (MCDM) technology is proposed. The fitting test criterion is taken into consideration in the method. For each candidate threshold, the fitting values of several fitting test criteria are integrated into a comprehensive evaluation value through entropy method and MCDM technology. The threshold corresponding to the minimum comprehensive evaluation value is assumed as the optimal threshold. A random simulation study is carried out to evaluate the performance of the method and to compare them with other literature methods. Genuine load data are applied the proposed method. Both the results shown that the proposed method could be seen as an additional method that complements existing threshold selection methods.

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 comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey

2021 ◽  
Vol 9 (2) ◽  
pp. 81
Author(s):  
Sami Özcan ◽  
Ali Kemal Çelik
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Entropy Method ◽  
Sensitivity Analyses ◽  
Food Sector ◽  
Relational Analysis ◽  
Machine Selection ◽  
Order Preference ◽  
Topsis Technique ◽  
Grey Relational

<div data-canvas-width="540.0693333333334">The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.</div>

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

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