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Journals / Düzce Üniversitesi Bilim ve Teknoloji Dergisi / 2016 / Cilt: 4 - Sayı: 2

Minimum Cost Optimization in Turning Operations

Tornalama İşlemlerinde Minimum Maliyet Optimizasyonu

Yasin CANTAŞ
Sezgin KAÇAR
Burhanettin DURMUŞ
Pages
424–430
Publication Date
2016-03-11
DOI
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AI Summary & Key Takeaways

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

Chaotic weighted PSO has achieved a lower cost compared to results in the literature.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, weighted chaotic PSO (Particle Swarm Optimization) algorithm is used to determine the parameters to provide a minimum cost in turning.
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Key Findings & Data:The objective of the problem defined by Shin and Joo is to determine the minimum cost of the multi-pass turning mathematical formula.
💡
Conclusion & Impact:Chaotic weighted PSO has achieved a lower cost compared to results in the literature.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Tornalama · minimum maliyet · parçacık sürü optimizasyonu

Abstract

In this study, weighted chaotic PSO (Particle Swarm Optimization) algorithm is used to determine the parameters to provide a minimum cost in turning. The objective of the problem defined by Shin and Joo is to determine the minimum cost of the multi-pass turning mathematical formula. Chaotic weighted PSO has achieved a lower cost compared to results in the literature.

Özet

Bu çalışmada, kaotik ağırlıklı PSO (Parçacık Sürü Optimizasyonu) algoritması, tornalama işlemlerinde minimum maliyeti sağlayacak parametreleri belirlemede kullanılmıştır. Problemin amacı, Shin ve Joo tarafından tanımlanan çok geçişli tornalama işlemlerine ait matematiksel formülün minimum maliyet değerini belirlemektir. Kaotik ağırlıklı PSO, literatürdeki sonuçlara göre daha düşük maliyet elde etmiştir.

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Cite This Article

CANTAŞ, Y., KAÇAR, S., DURMUŞ, B. (2016). Minimum Cost Optimization in Turning Operations. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, Cilt: 4 - Sayı: 2, 424–430. https://ajindex.com/articles/661025

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