LSWOA: 数値およびエンジニアリング設計の最適化問題のためのレヴィフライトとスパイラルフライトによる強化されたクジラ最適化アルゴリズム
Junhao Wei1, Yanzhao Gu1, Zhanxi Xie2
1Faculty of Applied Sciences, Macao Polytechnic University, Macao, China.
PloS one
|September 3, 2025
まとめ
改良されたクジラ最適化アルゴリズム (LSWOA) は,未熟な収束に対処し,探査を強化することで,元のものを改善します. この新しいアプローチは,ベンチマークとエンジニアリング最適化タスクの優れたパフォーマンスを示しています.
科学分野:
- コンピューター・インテリジェンス
- メタヒューリスティック最適化
- アルゴリズム強化
背景:
- クジラ最適化アルゴリズム (WOA) は,早めの収束,人口多様性の減少,遅い収束率,低精度などの制限に直面しています.
- 探査と採掘の段階の間の大きな不均衡は,複雑な最適化問題におけるWOAの有効性を妨げています.
研究 の 目的:
- 新しく改良されたクジラ最適化アルゴリズム (LSWOA) を導入し,正規のWOAの固有の制限を克服するように設計した.
- 全体の最適化性能,収束速度,およびWOAの精度を向上させる.
主な方法:
- より高品質な検索ベースラインのためのGood Nodes Set初期化を実装しました.
- 最適な脱出能力を強化するために 距離ベースの誘導捜索戦略を導入しました
- 探査と採掘のバランスをとるため,ダイナミックなパラメータ調整による強化されたスパイラルアップデート戦略を開発しました.
主要な成果:
- LSWOAは,他のメタヒューリスティックアルゴリズムとWOAの変数と比較して,さまざまな次元ベンチマーク機能の優れた最適化性能を示した.
- このアルゴリズムは 7 つのエンジニアリング設計最適化問題で優れた結果を達成し,実際のアプリケーションでの有効性を示しました.
- LSWOAはコンバージェンス速度と精度が向上し,複雑で高次元の最適化課題を効果的に解決しました.
結論:
- 提案されたLSWOAは,標準的なWOAの弱点を効果的に軽減し,より堅牢で効率的な最適化ツールを提供します.
- LSWOAは,その優れた性能と適応性により,現実世界のエンジニアリングの課題における多様なアプリケーションに重要な可能性を秘めています.
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