本文主要是針對供應鏈管理(supply chain management)加以探討，以往這一領域上的研究者，都是將討論的重心，放在訂貨策略(ordering policy)之議題上，使得存貨成本(inventory cost)降低，以及如何降低所謂的長鞭效應(Bullwhip effect)上。而所謂長鞭效應的意義，就是在一供應鏈系統中，即使顧客需求(customer demand)變異性不大，但當需求的資訊往上游傳遞時，便會一層一層被扭曲誇大，造成越上游的廠商誤以為其下游的客戶需求變異性非常大，因而做出不正確的訂貨策略或錯誤的生產規劃，使得廠商蒙受極大的生意損失。所以如何避免長鞭現象的發生，就成為研究供應鏈管理的專家學者所關心且極欲解決的課題。
首先，將使用時間系列(time series)的觀念，建立一套動態的供應鏈系統之數學模式，來清晰描述供應鏈的運作行為。然後推導顧客需求之預測模式，並採用系統控制理論(system control theory)，設計各種不同之控制器；因此本文將會對傳統控制器，例如比例控制器、比例積分控制器，甚至利用最小變異控制(MVC: minimum variance control)理論等，來推導適切訂貨預測器(ordering predictor)，最後再應用頻率分析(frequency analysis)的觀念，調諧出最佳的訂貨方式，並以電腦程式模擬其訂貨與出貨情形，藉以分析長鞭效應，並評估存貨控制的成效。結果顯示不管是傳統控制器，或者利用最小變異控制的理論所衍導的訂貨策略，皆比大家熟悉的訂貨策略(order up to level)，更能有效降低長鞭效應與做好存貨控制。尤其是最小變異控制器，不論顧客需求是固定的(stationary)或非固定的(non-stationary)，其控管訂貨與存貨的效率都是最佳的。

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