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Journals / ACADEMIC PLATFORM-JOURNAL OF ENGINEERING AND SCIENCE / 2020 / Cilt: 8 - Sayı: 3

Whale Optimization Algorithm for Numerical Constrained Optimization

Yuksel CELİK
Alper Talha KARADENİZ
Pages
547–554
DOI
—
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AI Summary & Key Takeaways

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

The experimental results show that WOA has low performance on constrained optimization.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Whale Optimization Algorithm (WOA), WOA is a recently developed, nature-inspired, meta-heuristic optimization algorithm.
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Key Findings & Data:The algorithm was developed in 2016, inspired by bubble hunting strategies used by humpback whales.
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Conclusion & Impact:The experimental results show that WOA has low performance on constrained optimization.
🔬Design:Modeling & Simulation
📍Scope:2016 Verileri
⚙️Variables:Domain Parameters

Özet

Whale Optimization Algorithm (WOA), WOA is a recently developed, nature-inspired, meta-heuristic optimization algorithm. The algorithm was developed in 2016, inspired by bubble hunting strategies used by humpback whales. To determine the performance of each optimization algorithm developed, they should be tested on a different type of optimization test problems. In this paper, we aim to investigate and analyse WOA logarithm on constrained optimization the performance and accuracy of the proposed method are examined on 13 (G1-G13) constrained numerical benchmark functions, and the obtained results are compared with other meta-heuristic optimization algorithms which taken from the literature. The experimental results show that WOA has low performance on constrained optimization.

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Cite This Article

CELİK, Y., KARADENİZ, A. T. (2020). Whale Optimization Algorithm for Numerical Constrained Optimization. ACADEMIC PLATFORM-JOURNAL OF ENGINEERING AND SCIENCE, Cilt: 8 - Sayı: 3, 547–554. https://ajindex.com/articles/354897

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