在一有多個工廠散布於各地的分散式製造環境當中，生產系統的複雜性相對提升，而產能規劃與資源分配議題，因會影響整個系統的表現，也越來越受到關注。本研究發展一整合式架構進行多廠區環境在有限資金下的配送。本研究建構依協商架構結合學習機制，進行自主配送總部所提供的有限資金，以及促進散布於單一廠區的有限製造資源的使用。由實驗顯示在與競爭對手協商時能有好的預測結果，因此證明本研究能有效縮短協商的時間。

In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performances. This study focuses on the development of an integrated framework to allocate limited budget in a multiple-factory environment. We develop a negotiation framework with learning mechanism to allocate autonomously finite budget provided by a headquarter and to facilitate the use of limited manufacturing resources that are scattered over individual factories. The outcome of the experiments shows good prediction of the opponent offers during negotiation, so it enables the reduction of negotiation time.

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