Determination of quality value of cotton fibre using hybrid AHP-TOPSIS method of multi-criteria decision-making

Majumdar, Abhijit; Sarkar, Bijan; Majumdar, Prabal Kumar

doi:10.1533/joti.2005.0013

Cited by 53 publications

(43 citation statements)

References 9 publications

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“…The MCDM approach was found to give better correlation between fibre quality and yarn strength. Hybrid AHP-TOPSIS method of MCDM approach was also found to be effective as shown by Majumdar et al [9] in their study for ranking the cotton fibres which gave good agreement with the ranking of yarn in terms of tenacity. Majumdar et al [10] in their another work has selected a suitable navel out of ten navels for denim fabrics using a combination of two popular MCDM approaches namely, TOPSIS and AHP.…”

Section: Some Application Of Mcdm Techniques In Textilesmentioning

confidence: 72%

Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

Choudhuri

2014

J. Inst. Eng. India Ser. E

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Multi-Criteria Decision Making is a branch of Operation Research (OR) having a comparatively short history of about 40 years. It is being popularly used in the field of engineering, banking, fixing policy matters etc. It can also be applied for taking decisions in daily life like selecting a car to purchase, selecting bride or groom and many others. Various MCDM methods namely Weighted Sum Model (WSM), Weighted Product Model (WPM), Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) and Elimination and Choice Translating Reality (ELECTRE) are there to solve many decision making problems, each having its own limitations. However it is very difficult to decide which MCDM method is the best. MCDM methods are prospective quantitative approaches for solving decision problems involving finite number of alternatives and criteria. Very few research works in textiles have been carried out with the help of this technique particularly where decision taking among several alternatives becomes the major problem based on some criteria which are conflicting in nature. Gradation of jute fibres on the basis of the criteria like strength, root content, defects, colour, density, fineness etc. is an important task to perform. The MCDM technique provides enough scope to be applied for the gradation of jute fibres or ranking among several varieties keeping in view a particular object and on the basis of some selection criteria and their relative weightage. The present paper is an attempt to explore the scope of applying the multiplicative AHP method of multi-criteria decision making technique to determine the quality values of selected jute fibres on the basis of some above stated important criteria and ranking them accordingly. A good agreement in ranking is observed between the existing Bureau of Indian Standards (BIS) grading and proposed method.

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Section: Some Application Of Mcdm Techniques In Textilesmentioning

confidence: 72%

Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

Choudhuri

2014

J. Inst. Eng. India Ser. E

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“…TOPSIS method is used for finding ideal solutions in these problems [12]. In order to solve the drawbacks and critics of the AHP, TOPSIS method is combined with AHP to produce the best solutions to difficult and complex MCDM problems such as performance analyzing [13], spaceflight planning [14], cotton quality determination [15] and agent-based recreational fishing [16]. In these studies, the optimized solutions are provided by combined AHP-TOPSIS methods effectively.…”

Section: Methodsmentioning

confidence: 99%

AHP-TOPSIS Method for Learning Object Metadata Evaluation

İnce¹,

Yi̇ği̇t²,

Işık³

2017

IJIET

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Abstract-Increasing usage of computers in educational systems such as web based learning systems cause huge e-content needs. In this context, Learning Objects (LOs), stored in Learning Object Repositories (LORs), are used to produce e-content and other educational materials. Evaluation and selection of LOs are difficult and time consuming process when LO and their descriptive metadata numbers are high. Therefore, LO selection process is considered as a multi criteria decision making (MCDM) problem. In this study, analytic hierarchy process -technique for order of preference by similarity to ideal solution (AHP-TOPSIS) methods are combined for selection of LOs from web-based Intelligent Learning Object Framework LOR that is called ZONESA. The results of the system, used in a real case study, showed that the proposed system can be used effectively to produce appropriate content using LO metadata.

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“…İdeal çözüm setinin bulunması aşağıdaki denklemde gösterilmiştir. (19) denkleminden hesaplanacak set A * = (V1 * , V2 * ,.. Vn * ) şeklinde gösterilebilir. Negatif ideal çözüm seti ise, V matrisindeki ağırlıklandırılmış değerlendirme faktörlerinin yani sütun değerlerinin en küçükleri (ilgili değerlendirme faktörü maksimizasyon yönlü ise en büyüğü) seçilerek oluşturulur.…”

Section: Tutarsızlık Oranının Belirlenmesiunclassified

OTOMOTİV SEKTÖRÜNDE FAALİYET GÖSTEREN BİR FİRMADA TEDARİKÇİ SEÇİMİ: AHP-BULANIK AHP ve TOPSIS UYGULAMASI

Alkan¹,

Aladağ²,

Çeli̇k³

2016

Beykent Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi

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ÖZETGünümüz global dünya pazarı gün geçtikçe daha yoğun bir hale gelmektedir. Bu yüzden günümüzdeki firmalar pazarda hayatta kalabilmek ve ürünleriyle rekabet edebilme yeteneklerini sürdürmek için üretim ve malzeme maliyetlerini düşürme yollarını aramaktadırlar. Maliyetlerin azaltılmasında en önemli unsur nitelikli tedarikçiden düşük fiyatlı ve kaliteli malzeme satın alınmasıdır. Bu çalışma tedarik zinciri yönetiminde önemli bir problem olan tedarikçi seçimi üzerinde odaklanmıştır. Amaç, otomotiv sektöründe faaliyet gösteren bir firmanın tedarikçi seçim sorununun çok ölçütlü bir yaklaşım ile değerlendirilmesidir. Çalışma iki aşamalı olarak planlanmış olup; ilk aşama otomotiv sektöründe tedarikçi seçiminde dikkat edilmesi gereken önemli ölçütlerin firmalarda anket çalışması yapılarak belirlenmesiyle başlamaktadır. Çalışmanın ikinci aşaması, mevcut olan ve aday olan tedarikçilerin çok ölçütlü yapıda değerlendirilerek göreceli olarak sıralanması aşamasıdır. Belirlenen ölçütler için en uygun tedarikçilerin seçiminde bulanık analitik hiyerarşi sürecinden yararlanılacaktır. Bu süreçte söz konusu tedarikçilerin belirlenen ölçütlere göre ağırlıklandırma ve seçimi işlemi Bulanık Analitik Hiyerarşi Prosesi ile yapılacaktır. Ayrıca tedarikçilerin öncelik sıralamalarının belirlenmesinde çok ölçütlü bir yaklaşım olan TOPSIS ve AHP yönteminden de yararlanılarak farklı bir bakış açısı sağlanmaya çalışılacaktır.

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Determination of quality value of cotton fibre using hybrid AHP-TOPSIS method of multi-criteria decision-making

Cited by 53 publications

References 9 publications

Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

AHP-TOPSIS Method for Learning Object Metadata Evaluation

OTOMOTİV SEKTÖRÜNDE FAALİYET GÖSTEREN BİR FİRMADA TEDARİKÇİ SEÇİMİ: AHP-BULANIK AHP ve TOPSIS UYGULAMASI

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