GWOA: エンジニアリングデザインの最適化のためのマルチ戦略の強化されたクジラ最適化アルゴリズム
Yanzhao Gu1, Junhao Wei1, Zikun Li2
1Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China.
PloS one
|September 3, 2025
まとめ
改善されたクジラ最適化アルゴリズム (GWOA) は,複雑な問題のグローバル検索とコンバージェンスを強化します. GWOAはベンチマークとエンジニアリング最適化タスクで優れたパフォーマンスを発揮し,より安定した効率的なソリューションを提供しています.
科学分野:
- コンピューター・インテリジェンス
- 最適化アルゴリズム
- メタヒューリスティック
背景:
- 伝統的なクジラ最適化アルゴリズム (WOA) は,局所的な最適化,遅い収束,および高次元問題の限定的なグローバル検索に苦しんでいます.
- 既存のWOAは,複雑な最適化シナリオでは,これらの制限を完全に解決できない可能性があります.
研究 の 目的:
- 改良されたクジラ最適化アルゴリズム (GWOA) を提案し,従来型のクジラ最適化アルゴリズムの欠点を解決する.
- 複雑な最適化問題のグローバル検索能力,収束速度,および解決精度を向上させる.
主な方法:
- 適応パラメータの調整,強化された獲物の囲み込み,およびシヌ・コシン検索戦略をWOAに統合する.
- 23のベンチマーク機能 (ユニモダル,マルチモダル,構成) とエンジニアリング設計問題 (圧力容器,スプリング) でGWOAをテストする.
- 基礎的なメタヒューリスティック,WOA変数,およびスケーラビリティ実験を含む最先端のアルゴリズムによる比較分析.
主要な成果:
- GWOAは,ほとんどのベンチマーク機能,特にマルチモダルおよび組成上の問題において,優れた収束速度と解の精度を示した.
- ベンチマークテストで74.46%の総合効率 (OE) を達成した.
- 効率的にコストを削減し,エンジニアリング最適化問題の制約を満たし,安定性と最適化能力を向上させました.
結論:
- GWOAは,マルチ戦略の統合により,グローバルな検索,コンバージェンス速度,およびソリューションの安定性を大幅に改善します.
- GWOAは複雑な最適化問題を解決する大きな可能性を示し,エンジニアリングアプリケーションの効率的なツールとして機能します.
- 提案されたGWOAは,従来の最適化アルゴリズムに強固で効果的な代替案を提供します.
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