改善された多戦略の均衡最適化器
Jianguo Yu1, Yanyang Lu2,3,4, Hamid Reza Karimi5
1Zhengzhou University of Aeronautics, School of Computer Science, Zhengzhou, 450046, China. yjg@zua.edu.cn.
Scientific reports
|August 23, 2025
まとめ
この研究は,新しい戦略でバランス最適化器 (EO) を強化し,グローバル検索と探索能力を向上させます. 強化された逆平衡状態 EO (R[Formula: see text]O) アルゴリズムは,ベンチマークテストと船舶の経路計画において優れたパフォーマンスを示しています.
科学分野:
- 最適化アルゴリズム
- ヒューリスティック・最適化
- コンピューター・インテリジェンス
背景:
- 標準均衡最適化器 (EO) は最適化能力に制限がある.
- 最適化アルゴリズムにおけるグローバル検索と探索の強化の必要性
研究 の 目的:
- 均衡最適化器 (EO) の性能を改善するために.
- EOの最適化能力とグローバル検索を強化するための新しい戦略を導入します.
- 改善されたアルゴリズムの有効性をベンチマーク機能と現実世界のアプリケーションで検証する.
主な方法:
- より広範な探査空間のための逆均衡状態のプールを実装する.
- 集中探査のための非均一な均衡状態選択戦略の導入
- 均衡状態の変異戦略を統合し,グローバル・オプティマム・サーチを強化する.
- 29のベンチマーク機能を用いた性能評価と,船舶の航路計画における応用
主要な成果:
- 強化されたEOは,逆均衡状態EO (R[Formula: see text]O) と呼ばれ,標準EOと比較して有意な性能改善を示している.
- R[Formula: see text]Oは,他のよく使用されるヒューリスティック最適化アルゴリズムと比較して優れた結果を示しています.
- 静的および動的障害を持つ水上船舶の経路計画におけるR[Formula: テキストを参照]Oの成功応用
結論:
- 提案された改良は,バランス最適化器の性能を効果的に改善します.
- R[Formula: テキストを参照]Oは,複雑な最適化問題に対する堅牢で効率的なソリューションを提供します.
- このアルゴリズムは 海洋車両の路線計画のような 自動運転システムの実用的な有用性を示しています
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