結合產品生命週期需求與售價及購買成本持續性遞減於最佳存貨策略之研究

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Title:	結合產品生命週期需求與售價及購買成本持續性遞減於最佳存貨策略之研究
Other Titles:	Optimal Replenishment Policy with PLC Demand under Continuous Unit Cost and Selling Price Decrease
Authors:	吳惠庭 WU, HUEI-TING
Contributors:	張炳騰 CHANG, PING-TENG 工業工程與經營資訊學系
Keywords:	產品生命週期;庫存策略;基因演算法;購買成本遞減;售價變動 Product Life Cycle;Genetic Algorithm;Replenishment Policy;Unit Cost decrease;Unit selling price decrease
Date:	2019
Issue Date:	2019-12-16T01:48:56Z (UTC)
Abstract:	存貨管理一向是企業的生產銷售活動中，用來估算成本，衡量進出貨績效的重要議題，而無論是單一工作站、單一部門或是整條供應鏈，於銷售的探討必定為如何進入市場、產量穩定後的趨勢走向分析，直至衰退產量降低，最終退出市場等等，此即為產品生命週期（Product Life Cycle）的理論，而不同的產品具有不同的產品生命週期型態，因此，在其中的趨勢變化，也就是產品在週期中的需求量變化，亦是企業相當注重的部分。目前，存貨相關的模型已發展出許多類型，但主要皆以單一的需求類型為主軸來做探討，但產品具有許多不同的需求變化與條件，且隨著時代的演進與科技進步，相似產品推陳出新的速度日益增快，僅做單一型態探討並無法及時的因應市場需求，因此，本研究利用產品生命週期做為需求量的變化趨勢，再加上基因演算法進行最佳化求解，分別以利潤極大化與成本極小化為目標，發展一數學模式，同時考量購買價格與售價固定、持續性遞減與分批等類型，經修正最後發展為本研究的目標函數，使用Matlab 2018b軟體做基因演算法的分析，透過上述方法，探討各需求型態下的購買價格與售價組合所產生的變化，並根據最佳解所求得之訂購時間點、訂購成本、利潤以及訂購次數進行分析。 Inventory management has always been an important issue in the production and sales activities of enterprises to estimate costs and measure the performance of incoming and outgoing shipments. Whether it is a single workstation, a single department or the entire supply chain, the discussion of sales must be how to enter the market and output. The trend after stabilization goes to analysis until the decline in production declines, and finally exits the market, etc. This is the theory of Product Life Cycle, and different products have different product life cycle patterns, so in which The change in trend, that is, the change in demand during the cycle of the product, is also a part of the company's considerable focus.At present, inventory-related models have been developed in many types, but mainly based on a single demand type as the main axis, but the products have many different demand changes and conditions, and with the evolution of the times and technological advancement, similar products are emerging. The speed is increasing, and only a single type of discussion can not meet the market demand in time. Therefore, this study uses the product life cycle as the trend of demand, and then the genetic algorithm is used to optimize the solution. With the goal of maximizing profits and minimizing costs, we will develop a mathematical model, taking into account the types of purchase price and fixed price, continuous declining and batching, and finally develop the objective function of this study, using Matlab 2018b software to make genes. Through the above method, the algorithm analyzes the changes in the purchase price and price combination under various demand types, and analyzes the order time, order cost, profit and order quantity obtained from the best solution.
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