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Journals / Bilişim Teknolojileri Dergisi / 2021 / Cilt: 14 - Sayı: 4

Evaluation of the Most Valuable Player Algorithm for Solving Real-World Constrained Optimization Problems

Gerçek Dünya Kısıtlı Optimizasyon Problemlerinin Çözümü için En Değerli Oyuncu Algoritmasının Değerlendirilmesi

Sait Ali UYMAZ
Pages
345–353
Publication Date
2021-10-31
DOI
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AI Summary & Key Takeaways

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

The results showed a high success rate in finding feasible solutions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Real-world constrained optimization problems have constraints and local minimums in addition to decision variables.
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Key Findings & Data:In this study, the MVPA algorithm is combined with constraint handling techniques and some modifications and tested on 19 real-world constrained engineering optimization problems.
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Conclusion & Impact:The results showed a high success rate in finding feasible solutions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Kısıt işleme tekniği · Mühendislik problemleri · en değerli oyuncu algoritması

Abstract

Real-world constrained optimization problems have constraints and local minimums in addition to decision variables. They are time consuming and difficult to solve since the search spaces of these problems are very small due to the constraints. In recent years, many new metaheuristic algorithms have been proposed and combined with constraint handling techniques to solve such problems. The most valuable player algorithm (MVPA), a recently proposed metaheuristic optimization algorithm, inspired by sports events, has been tested on mathematical benchmark functions. In this study, the MVPA algorithm is combined with constraint handling techniques and some modifications and tested on 19 real-world constrained engineering optimization problems. The results showed a high success rate in finding feasible solutions.

Özet

Gerçek-dünya kısıtlı optimizasyon problemlerinin, karar değişkenlerine ek olarak kısıtlamaları ve yerel minimum noktaları vardır. Kısıtlamalar nedeniyle bu problemlerin arama alanları çok küçük olduğu için çözülmesi zor ve zaman alıcıdır. Son yıllarda, bu tür problemleri çözmek için birçok yeni meta-sezgisel algoritma önerilmiş ve kısıt işleme teknikleriyle birleştirilmiştir. Spor etkinliklerinden esinlenerek yakın zamanda önerilen bir meta-sezgisel optimizasyon algoritması olan En Değerli Oyuncu Algoritması (MVPA), matematiksel test fonksiyonları üzerinde test edilmiştir. Bu çalışmada, MVPA algoritması kısıt işleme teknikleri ve bazı modifikasyonlar ile birleştirilerek 19 kısıtlı gerçek dünya mühendislik optimizasyon problemi üzerinde test edilmiştir. Sonuçlar, kısıtları sağlayan uygun çözümler bulmada yüksek bir başarı oranı göstermiştir.

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Cite This Article

UYMAZ, S. A. (2021). Evaluation of the Most Valuable Player Algorithm for Solving Real-World Constrained Optimization Problems. Bilişim Teknolojileri Dergisi, Cilt: 14 - Sayı: 4, 345–353. https://ajindex.com/articles/382022

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