本研究針對供應鏈中多廠生產規劃的問題進行研究，為了彌補現行企業採用的經驗法則之不足，首先運用混合型整數線性規劃，建構「單階決策模式」，而為了降低問題的複雜度及運算時間，乃進而建構「二階決策模式」。單階決策模式以成本極小化為目標式，考量產能限制與物料限制，可求出企業最佳的生產規劃與資源分配。二階決策模式則是將單階決策模式中所考量的成本與限制分成兩個階段考量：第一階段為「訂單分配階段」；第二階段為「工廠規劃階段」。透過系統化之情境設計與模擬分析，可得以下結論：1. 單階決策模式能得到最佳的生產規劃計畫，但運算耗時，不適合實務應用。2. 二階決策模式能求得接近最佳的生產規劃計畫，運算時間合理，若配合企業其他供應鏈管理方案，可提升企業整體營運效能。

The production planning among many sites is one of the key supply chain management issues. In this research, two decision support models for multi-plant production planning based on mixed-integer linear programming techniques are developed. The first one is a “monolithic model” that considers both the capacity and material constraints and provides an optimal production plan to minimize the overall production cost. The second one is “two-stage model”, which first allocates the customers' orders to different plants under the capacity constraint and the minimum cost objective. With the orders being determined, then in the second stage a different model is used to provide the optimal production plans for individual plants under the material and capacity constraints. Results of simulation study show that the two-stage decision support model is superior and provides the near optimal solutions and requires a very efficient computation effort.