應用螞蟻演算法建構多階序列式整合即時化存貨模型

Applying Ant Colony Optimization Algorithm in a Serial Multi-echelon Integrated Just-in-Time Inventory Model

邱柏鈞(Po-Chun Chiu)

指導教授 ： 林志平

國立臺北科技大學/管理學院/工業工程與管理系碩士班/碩士(2014年)

https://doi.org/10.6841/NTUT.2014.00687

摘要

隨著全球產業競爭加劇，各家企業正面臨著諸多挑戰，如何快速地反應顧客的實際需求與有效地降低成本為管理階層所重視之焦點。在傳統的存貨管理之中，上、下游廠商各自追求本身成本的最小化而並非整體供應鏈之利益最佳化。因此，本研究提出一運送前置時間不確定及品質不可靠環境下之多階序列式整合即時化存貨模型，在供應鏈中各階層成員可以交換相關資訊的條件下同時進行生產、採購和運送等決策，以達成整體供應鏈總成本最小化之目標。此類NP-hard 問題通常無法以傳統數學方法解決，因此本研究提出一數值範例並採用螞蟻演算法求解，並與粒子群演算法進行效益比較，最後提出不同參數環境下的敏感度分析。
本文提出之整合存貨模型，是非常符合現實環境下的存貨模式，基於各現實情境下的整合，並以演算法求解是現今存貨模型的趨勢，也能成為企業的參考依據。

關鍵字

整合存貨模型 ； 不良品 ； 前置時間不確定 ； 存貨策略決策

並列摘要

In this highly competitive global environment, the profit of the whole supply chain is more essential than a single echelon member. Some purchasers may be far away from their vendors geographically, which causes the uncertain delivery lead time. The length of the lead time affects the customer service level, inventory investment in safety stock, and the core competitive ability of an enterprise. The inventory level would be influenced through the number of defective items found by purchaser as well. Therefore, the objective of this research is to find out an optimal inventory policy minimizing the joint total cost of the entire supply chain under the circumstances of uncertain delivery lead time and quality unreliability. We proposed an algorithm of ant colony optimization to find out the best solution, comparing with the efficiency of Particle Swarm Optimization, making the sensitive analysis between several parameters and the total cost. Applying algorithm is the tendency of novel inventory model, which could be the reference of enterprises as well.

並列關鍵字

integrated inventory model ； unreliable quality ； uncertain delivery lead time ； strategy of inventory

參考文獻

[1] S. K. Goyal, "An Integrated Inventory Model for a Single-supplier

15, 1977, pp. 107-111.

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[4] F. Chen, "Optimal Policies for Multi-Echelon Inventory Problems with Batch