考量運輸成本及搬產能限制之合併補貨問題

Abstract

合併補貨問題(Joint Replenishment Problem, JRP) 主要藉由產品的合併補貨以降低產品的平均總成本。本研究為考慮運輸成本及搬運產能限制的合併補貨問題，除了考量傳統JRP問題具有的成本項目之外，另外加入運輸成本項。本研究建構了一個具有整備成本、存貨成本以及運輸成本的JRP數學模式，並針對數學模式進行理論分析，且運用基因演算法為整體求解架構，結合自行發展的一套搜尋最佳基本週期(B值)之演算機制，求得在滿足搬運產能的可行性限制之下的最佳基本週期(B值)、各產品的補貨週期乘數與對應之補貨排程期別、以及各排程期別之下所需要的貨車數量，達到整備、存貨、運輸成本最小化的目標。此外，本研究亦會運用共同週期法(Common Cycle Approach, CC)進行實驗數據的比較，以數據實驗證明本研究所發展之求解演算法為一優良的求解方法。

The conventional Joint Replenishment Problem (JRP) considers the following cost terms: (1) major setup cost, (2) minor setup cost and (3) holding cost. This study focuses on the extension of the JRP by taking into account the container transportation cost and the capacity constraints of the material handling facilities. We formulate a mathematical model for the concerned problem. Also, we conduct theoretical analysis for the transportation cost with respect to the number of required containers and the value of the basic period. Our theoretical results facilitate in proposing a search procedure for seeking an optimal and feasible basic period for a given set of multipliers. By encoding the set of multipliers, we propose a genetic algorithm (GA) that incorporates with the proposed search procedure. Following our numerical experiments, we conclude that the proposed GA is an effective solution approach that obtains excellent solutions for the concerned JRP.