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Performance evaluation of sugar plants by fuzzy technique for order performance by similarity to ideal solution (topsis)

Cybernetics and Systems · Eylül 2012

Özet
This study presents the performance evaluation of sugar plants using the technique for order performance by similarity to ideal solution (TOPSIS) under a fuzzy environment. First, the decision criteria used to evaluate the performances are determined, and then the data from financial statements are collected from sugar plants. Accordingly, the ratings of various alternatives under various criteria and the importance weights of various criteria are assessed by evaluators using linguistic terms. The data obtained are converted into a fuzzy triangular number system and then the fuzzy TOPSIS method is applied to make a final decision. According to the closeness coefficients, the sugar plants are ranked from strong to weak. A real case study involving eight evaluation criteria and nine sugar plants assessed by nine evaluators is provided to illustrate the proposed method. The results show that this method is an effective tool for evaluating investment risks based on the heuristic knowledge acquired from experts. © 2012 Copyright Taylor and Francis Group, LLC.
10 atıf Eylül 2012 DOI
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YÖKSİS Kayıtları
PERFORMANCE EVALUATION OF SUGAR PLANTS BY FUZZY TECHNIQUE FOR ORDER PERFORMANCE BY SIMILARITY TO IDEAL SOLUTION TOPSIS
Cybernetics and Systems · 2012 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Bu dergide (ISSN eşleşmesi) kurumun 3 kaydı bulundu.
A COMPARATIVE STUDY ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHMS FOR TRAVELING SALESMAN PROBLEMS
2009 ISSN: 0196-9722 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
PERFORMANCE EVALUATION OF SUGAR PLANTS BY FUZZY TECHNIQUE FOR ORDER PERFORMANCE BY SIMILARITY TO IDEAL SOLUTION TOPSIS
2012 ISSN: 0196-9722 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Chaotic Levy-Flight-Driven Siberian Tiger Optimization for Enhanced Data Clustering
2026 ISSN: 0196-9722 SCI-Expanded Q3
Doç. Dr. TAHİR SAĞ →

Makale Bilgileri

Toplam Atıf 10 atıf · Scopus
ISSN01969722
Yayın TarihiEylül 2012
Cilt / Sayfa43 · 529-548

Kurumlar

Kırşehir Ahi Evran Üniversitesi
Kirsehir Turkey
Selçuk Üniversitesi
Selçuklu Turkey

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Scimago Dergi (ISSN Eşleşmesi)
Cybernetics and Systems
Q2
SJR Skoru0,469
H-Index51
YayıncıTaylor and Francis Ltd.
ÜlkeUnited Kingdom
Artificial Intelligence (Q2)
Information Systems (Q2)
Software (Q3)
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10
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