【摘要】：供應(yīng)鏈上下游企業(yè)可以視為買方與賣方的關(guān)系,上游企業(yè)不考慮下游企業(yè)的需求容易導(dǎo)致企業(yè)之間的供需失衡。因此研究上下游企業(yè)之間的生產(chǎn)銷售問題,以實(shí)現(xiàn)長期運(yùn)行情況下每個(gè)企業(yè)利潤最高,對(duì)于實(shí)際供應(yīng)鏈有重要意義。首先,論文建立了一種基于單零售商需求驅(qū)動(dòng)的生產(chǎn)銷售系統(tǒng)。該系統(tǒng)包括一個(gè)上游企業(yè)(生產(chǎn)商)和一個(gè)下游企業(yè)(零售商),兩個(gè)企業(yè)擁有獨(dú)立的庫存單元和決策過程。生產(chǎn)商可以視為基于需求驅(qū)動(dòng)的傳送帶給料加工站系統(tǒng),成品庫庫存狀態(tài)受零售商補(bǔ)貨訂單和自身生產(chǎn)能力共同影響。生產(chǎn)商的控制變量為加工站點(diǎn)的前視距離,優(yōu)化目標(biāo)是尋找到最優(yōu)的前視控制策略,考慮到系統(tǒng)中工件到達(dá)時(shí)間、工件加工時(shí)間難以準(zhǔn)確獲知,論文采用一種與模型無關(guān)的強(qiáng)化學(xué)習(xí)算法對(duì)生產(chǎn)商的最優(yōu)或者次優(yōu)前視控制策略進(jìn)行求解。零售商采取動(dòng)態(tài)補(bǔ)貨策略,庫存狀態(tài)受隨機(jī)的顧客需求和生產(chǎn)商的實(shí)際補(bǔ)貨量共同影響。零售商的控制變量為補(bǔ)貨點(diǎn),優(yōu)化目標(biāo)是尋找到最優(yōu)的庫存控制策略,由于顧客需求的動(dòng)態(tài)隨機(jī)性,論文采用強(qiáng)化學(xué)習(xí)算法對(duì)零售商的優(yōu)化控制問題進(jìn)行求解�？紤]到實(shí)際情況中生產(chǎn)商通常給多個(gè)零售商補(bǔ)貨,論文進(jìn)一步研究了一種多零售商生產(chǎn)銷售系統(tǒng)的優(yōu)化控制。系統(tǒng)中多個(gè)零售商之間存在靜態(tài)博弈關(guān)系,即每個(gè)零售商的補(bǔ)貨需求在時(shí)間上有先后順序,并且各零售商不知道其余零售商的補(bǔ)貨策略。生產(chǎn)商根據(jù)補(bǔ)貨訂單的時(shí)間順序即時(shí)完成配貨后,成品庫狀態(tài)相應(yīng)發(fā)生改變。最后論文采用強(qiáng)化學(xué)習(xí)算法分別對(duì)生產(chǎn)商和多個(gè)零售商的最優(yōu)或者次優(yōu)控制策略進(jìn)行求解,并從顧客到達(dá)率、倉庫容量和補(bǔ)貨期三方面對(duì)多零售商之間的博弈關(guān)系進(jìn)行了分析。
[Abstract]:The upstream and downstream enterprises of supply chain can be regarded as the relationship between buyer and seller, and the upstream enterprises do not consider the demand of downstream enterprises, which leads to the imbalance of supply and demand between enterprises. Therefore, it is of great significance to study the production and sales problems between upstream and downstream enterprises in order to realize the highest profit of each enterprise in the long run. Firstly, a production and sales system based on demand driven by single retailer is established. The system consists of an upstream enterprise (manufacturer) and a downstream enterprise (retailer). The two enterprises have independent inventory units and decision-making process. The manufacturer can be regarded as a demand-driven delivery and delivery station system, and the inventory status of the finished product store is affected by the retailer's replenishment order and its own production capacity. The manufacturer's control variable is the forward distance of the processing station. The optimization goal is to find the optimal forward view control strategy. Considering the arrival time of the workpiece in the system, the processing time of the workpiece is difficult to be accurately determined. In this paper, a model independent reinforcement learning algorithm is used to solve the optimal or suboptimal forward view control strategy. The retailer adopts dynamic replenishment strategy and the inventory status is affected by the random customer demand and the actual replenishment volume of the manufacturer. The retailer's control variable is restocking point, and the optimization goal is to find the optimal inventory control strategy. Because of the dynamic randomness of customer demand, the reinforcement learning algorithm is used to solve the optimal control problem of retailer. Considering that manufacturers usually replenish more than one retailer in practice, this paper further studies the optimal control of a multi-retailer production and sales system. There is a static game relationship among many retailers in the system, that is, the replenishment demand of each retailer has an order in time, and each retailer does not know the replenishment strategy of the other retailers. The state of the finished goods warehouse changes immediately after the manufacturer completes the distribution according to the time order of the replenishment order. Finally, the reinforcement learning algorithm is used to solve the optimal or sub-optimal control strategy of manufacturers and multiple retailers, and the game relationship between multiple retailers is analyzed from three aspects: customer arrival rate, warehouse capacity and replenishment period.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F274

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