在現今競爭激烈的環境下,如何在每一次的補貨中節省成本是零售商欲達成的目標。本研究主要是探討零售商在延遲付款下,多品項商品的補貨決策問題。本研究的目標在於求得零售商的最佳補貨週期以最小化總成本,並藉由納入延遲付款與多品項來延伸傳統的經濟訂購批量模型,以反映現實生活中的商業情形。我們先分別建立了在延遲付款之下的多品項個別補貨、多品項直接分群策略的聯合補貨模式及多品項間接分群策略的聯合補貨模式,之後分別對各補貨模式求解或發展演算法,最後藉由數值範例說明求解步驟並提出結論。在本研究可發現,在允許延遲付款之多品項直接分群策略的聯合補貨模式比個別補貨決策更能最小化總成本;而在允許延遲付款之多品項間接分群策略的聯合補貨模式中,極值搜尋的啟發式演算法比成本平衡的啟發式演算法更有效率。本研究的結果將提供給管理者在決策上有利參考之依據。
In today’s severely competitive business environment, how to reduce replenishment cost is one of the most important objects for retailers. This study deals with policy making of joint multi-item replenishment under conditions of permissible delay in payments. Our objective is to seek out the optimal replenishment cycle policy for retailers in order to minimize their total cost. We extend the traditional EOQ model by putting into considerations of the situations of permissible delay in payments and multi-item replenishment so as to better reflect the real-world business situation. We also present three replenishment models, including single-item replenishment, joint multi-item replenishment for direct grouping strategies and joint multi-item replenishment for indirect grouping strategies, and develop solutions or algorithms for each model. Finally, through numerical examples, we illustrate the solution procedures and draw conclusions. In this study we find that joint multi-item replenishment for direct grouping strategies is better than single-item replenishment in minimizing the total cost; while in joint multi-item replenishment for indirect grouping strategies model, extreme-finding heuristic is more efficient than cost-balancing heuristic in finding out optimal replenishment frequency. The results of this study will serve as references for business managers or administrators while making decisions in their favor.