考慮壅塞與多出口之物流中心儲位配置

Abstract

近年來，因為各種產品的不斷推陳出新來滿足顧客的多樣化需求，供應鏈管理著重於降低成本以及降低產品推出至市場的時間。由於消費者習慣日漸改變為要求少量多樣、快速且可靠的訂單，因此物流中心執行訂單之效率成為相對重要的一項課題。物流中心的倉儲作業中，揀貨是最勞力密集且最耗時間之作業，故提升揀貨作業之效率為物流中心降低成本、改善效率之首要目標。雖然將產品指派至適當位置為最能夠影響揀貨效率之有效方法，但以往儲位配置相關文獻中大多僅考慮產品訂單頻率，而忽略了產品間具有的屬性關係及實務上揀貨作業執行時所可能遇到的實際問題，故有鑑於此，本論文將研究產品間之屬性關係與實務上所遇到之相關問題進行研究討論。 本研究使用資料探勘中之關聯法則分析產品間之屬性關係，並且發展出儲位配置最佳化指標，該指標除了考慮產品加權支持度外，亦結合儲位與多個出口間的平均距離及產品週轉率，並結合實務上會遇到的揀貨壅塞問題，以二元整數規劃方法建構出一「儲位配置最佳化決策模式」，並透過實際的訂單資料求解壅塞限制與多出口限制下之儲位配置決策問題。分析結果顯示，考慮壅塞限制下之目標值會較不考慮壅塞限制下之目標值為低，表示產品之儲存位置在考慮壅塞限制時會將產品擺放至其他較遠離出口之位置，進而減緩壅塞發生之頻率。

In recent years, because enterprises launch a series of new products to satisfy the variety of demand of customers, reducing both costs and time-to-market becomes an important role in supply chain management. Due to the rapidly changing preferences of customers, customer orders increasingly exhibit characteristics of higher product variety, smaller order size and reliably shorter response time. Such changes to order patterns challenge the efficiency of distribution center order fulfilment processes in today’s highly competitive market. Although among distribution center’s activities, order picking is the most labour-intensive and time-consuming operation with manual systems, order picking becomes the first thing to increase the effectiveness of distribution center. Although there are many approaches to increase the effectiveness of order picking, storage assignment approach is more influential than any of the other approaches. According to past reference, most studies of correlated storage assignment approaches are considering that products are frequently ordered together should be assigned locations that are close to each, but these approaches ignore the property relations between the products and some real problems which may encounter in order picking. In view of this, this thesis will study the property relations between the products and some problems in real order picking activities. This thesis analyze the property relations between the products by means of association rule of data mining, and construct the “optimal association index of storage assignment”. The “optimal association index of storage assignment” will include weighted support between products, the average distance between location and multi-exit and turnover rate of products. Then this thesis will construct the “optimal model of decision for storage assignment”, based on Binary Integer Programming (BIP), and consider congestion problem which may encounter in order picking. Then this thesis will use the real order data to test simulated samples. The conclusion of the analysis has shown that the objective value in considering congestion constraints is lower than non-considering congestion constraints, which means considering congestion constraints will make product choose farer locations to avoid the frequency of congestion.