Journals / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2015 / Cilt: 33 - Sayı: 3

MULTI-OBJECTIVE SIMULATION OPTIMIZATION USING GREY-BASED TAGUCHI METHOD WITH FUZZY AHP WEIGHTING

Pages
341–350
Publication Date
2015-09-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Additionally, in the stage of grade relational calculation of grey relational analysis (GRA) fuzzy AHP weighting process is adopted to determine the weights of grey relational coefficients.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Simulation is a powerful tool for analyzing and designing of industrial and service systems.
📊
Key Findings & Data:But simulation can’t optimize the system elements and needs additional methods for optimization.
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Conclusion & Impact:Additionally, in the stage of grade relational calculation of grey relational analysis (GRA) fuzzy AHP weighting process is adopted to determine the weights of grey relational coefficients.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Multi-objective simulation optimization · grey-based Taguchi · fuzzy AHP

Abstract

Simulation is a powerful tool for analyzing and designing of industrial and service systems. But simulation can’t optimize the system elements and needs additional methods for optimization. In this study a multi-objective simulation optimization is dealt with. To determine the optimum factor levels, grey-based Taguchi approach is used. Since Taguchi method is designed for single objective problems, grey relational analysis is combined with Taguchi method to solve this multi-objective simulation optimization problem. Additionally, in the stage of grade relational calculation of grey relational analysis (GRA) fuzzy AHP weighting process is adopted to determine the weights of grey relational coefficients.

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Cite This Article

BELGİN, Ö. (2015). MULTI-OBJECTIVE SIMULATION OPTIMIZATION USING GREY-BASED TAGUCHI METHOD WITH FUZZY AHP WEIGHTING. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 33 - Sayı: 3, 341–350. https://ajindex.com/articles/419382

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