第五章 模式驗證與應用
6.2 建議
針對本研究相關結果，於此提出相關研究建議，內容如下：
（一）模式設計方面
1. 由於本研究並無考量到任何外在限制對於存貨的影響，基於存貨管理也是一作業研究 的概念，若產生相關限制，則將無法進行微分求解，故強烈建議以作業研究的方式進 行存貨管理，但仍可將本研究研擬出之模式考量其中，並且在限制容許範圍內，仍可 進行微分計算。
2. 本研究的分群的屬性依據是以成本考量為出發點，對於許多物料固有的基本性質卻無 法加以考量。由於最佳存貨策略研擬在於視物料的屬性找尋合適的存貨方式，故對於 物料的許多基本性質都必須加以瞭解，方能設計出較佳的存貨方式，並擬出對整體而 言最佳的存貨策略。若能把物料在存貨管理中大部份基本性質利用模式的方式表現出 來或在分群方式中予以考量，對於接近最佳存貨策略之研擬必能再跨一大步。
（二）資料與數據處理方面
1. 本研究並無提供一確切實例進行模式驗證，雖用變數產生器進行資料產生，但實務情 形則較無法掌握，建議往後相關研究可以原物料為主，進行資料收集之工作。
2. 本研究在單位倉儲成本設定上較為單純，是以存放體積大小來做為計算的標準，但就 一般存貨理論中，對於單位倉儲成本的設定，多半會考慮到物料的體積、市場價格、
保險、折舊等詳細項目，也由於設定上較為單純，研究中倉儲成本占存貨成本的比例 十分小，若能妥善考量到較為主要的影響因素，進而建立良好的參數，對於存貨模式 的構建與存貨策略的研擬皆相當有幫助。
3. 規模係數的訂定較為固定，原因在於想降低各規模係數對於在存貨方式選擇上的影響 程度，但是就也許規模係數也會隨著倉儲量或配送量的改變而變動，故建議往後相關 研究，必須要先就規模係數進行校估的工作。
（三）分群方式的配合
1. 基因演算法逐步分群方式有處理變數規模上的限制，在變數超過相當數量時，分群模 式將無法進行分群及計算出經濟訂購比例，但逐步分群方式的優勢卻不容忽視。建議 日後對於逐步分群方式，研擬出更有效率的編碼及運算方式，以解決運算時間過長及 處理規模限制等問題。
2. 統計分群的方式雖然較逐步分群方式為差，但對於供應鍊管理而言，統計分群的方式 對於物料處理來說較易建立管理上的理論，換言之即較為找出何種物料適用於何種存 貨管理方式或系統，故也建議往後相關之存貨研究，可運用統計分群的方式進行較準 確或詳細的物料分類，使得供應鍊的功能更能發揮。
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