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多シナリオのハイブリッドフローショップスケジューリングの問題の解決改良された探査機モデルに基づいて

Xiang Tian¹, Yang Kong¹, Xiyu Liu^2,3

¹School of Health Management, Binzhou Medical University, Yantai, Shandong, China.

|September 3, 2025

まとめ

この研究は,ハイブリッドフローショップスケジューリングの問題のための多層プローブ操作 (IPMMPO) を備えた改良プローブマシンを導入します. 新しいIPMMPO-CPモデルは既存のアルゴリズムとモデルを大幅に上回ります.

科学分野:

運用研究
コンピュータ科学
産業工学

背景:

ハイブリッドフローショップスケジューリング (HFS) は,製造業と生産業界において極めて重要です.
探査機は複雑な最適化タスクのための高度なコンピューティング機能を提供します.
既存の方法は,HFSの問題のさまざまなシナリオと闘っています.

研究の目的:

マルチシナリオのハイブリッドフローショップスケジュールの問題を解決するための新しいアプローチを開発する.
多レベルプローブ操作 (IPMMPO) とその制約プログラミング (CP) モデル (IPMMPO-CP) を導入する.
様々なHFS問題タイプに合わせたデータとプローブライブラリを作成します.

主な方法:

HFSシナリオ (同一の/関連のない並列マシン,待機なし/標準) のための一般的なデータとプローブライブラリを設計した.
データ前処理として制約プログラミング (CP) モデリングのためのツプルセットを開発した.
マルチシナリオのHFS問題に対するIPMMPO-CPモデルを提案した.

主要な成果:

IPMMPO-CPモデルは,幅広いHFS問題インスタンスで優れたパフォーマンスを示しました.
比較分析により,IPMMPO- CPは9つの代表的なアルゴリズムと2つの最近のCPモデルに優れていることが示されました.
提案された方法は,同一の並列マシン,無関係な並列マシン,および待機制約を効果的に処理します.

結論:

IPMMPO-CPは,複雑なハイブリッドフローショップスケジューリングのための強力で汎用的なソリューションを提供します.
開発されたデータとプローブライブラリは,プローブマシンのHFSへの適用性を高めます.
この研究は,マルチシナリオのHFS問題を解決する最先端の技術を進めている.

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