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Pelican Optimization Algorithm: A Novel Nature-Inspired Algorithm for Engineering Applications

📅 Published: January 23, 2022 👤 Pavel Trojovský, Mohammad Dehghani 📖 Sensors 📊 842 citations
AI-Generated Summary

Optimization is an important and fundamental challenge to solve optimization problems in different scientific disciplines. The findings of POA are compared with eight well-known metaheuristic algorithms to assess its competence in optimization.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 In this paper, a new stochastic nature-inspired optimization algorithm called Pelican Optimization Algorithm (POA) is introduced.
  • 2 The main idea in designing the proposed POA is simulation of the natural behavior of pelicans during hunting.
  • 3 In POA, search agents are pelicans that search for food sources.
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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