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库存与配送联合优化若干问题研究

Research on Integrated Optimization Problems of Inventory and Transportation

【作者】 刘桂庆

【导师】 周永务;

【作者基本信息】 合肥工业大学 , 管理科学与工程, 2011, 博士

【摘要】 库存成本和配送成本是供应链成本的重要组成部分,库存管理和配送管理因而成为供应链管理中的两个重要方面。由于现实情形复杂多变,增大了供应链上库存问题与配送问题的复杂性,因此传统的企业或供应链运作方面的文献通常将库存与配送分割开来进行研究。供应商管理库存为供应链管理提供了一种新的运作模式。在这种模式下,供应商通过先进的信息技术及时准确地掌握供应链下游零售商的库存信息,从而能够从系统角度优化供应链上的整体库存,并构建合理的配送方案。然而现有文献一般针对一体化供应链情形,理论研究成果难以运用到实际的供应链。本文主要针对非一体化的供应链,研究供应商管理库存模式下库存与配送联合优化时存在的若干问题,主要研究工作和创新点如下:(1)研究了库存与配送联合优化时的最优订货问题。针对需求确定情形下的单供应商和单零售商组成的二级非一体化供应链,分别为独立决策、联合决策以及基于价格折扣策略非一体化供应链的协调方式等三种情形建立了数学模型并构造了相应的求解算法。数值算例结果表明采用价格折扣策略能够使得供应链整体利润接近一体化理想情形,并确保供应商和零售商双方的利润均得到提高,从而促进供应商与零售商合作。(2)研究了库存与配送联合优化时运输成本的支付问题。针对单供应商单零售商的二级供应链,研究了库存与配送联合优化时由谁承担运输成本的问题。考虑了一体化供应链的理想情形以及运输成本分别由供应商、零售商承担三种情况,并为此三种情况建立了数学模型。随机数据实验表明,零售商承担运输成本时可获得相对较优的供应链整体利润,其值接近于理想情况下供应链的总体利润,进而采用利润分配策略,能够确保供应商和零售商双方均获得更大利润。(3)研究了库存与配送联合优化且考虑弹性需求时的定价问题。假设供应商在供应链中占主导地位,针对弹性需求环境,并同时考虑定价、库存和运输成本,分析了非合作决策时定价模型以及一体化联合决策模型,然后分别运用收益共享和价格折扣两种不同的协调策略来分配利润,确保双方合作。实验结果表明,与供应商-Stackelberg博弈下的非合作决策相比,一体化联合决策能大大提高系统利润,运用收益共享和价格折扣策略均可改善供应链整体运作的协调性,可以将供应链系统增加的利润合理分配给零售商和供应商,以确保双方利润均高出非合作决策时的利润。(4)研究了不考虑供应商库存成本的库存路径问题。针对由单一供应商和多零售商组成的二级供应链系统,建立了库存与运输联合优化的数学模型,构造了改进的最邻近算法以降低运输费用和库存成本,提高供应链的整体利润。设计了价格策略,即给出了调整价格的上限和下限,可作为供应商和各零售商价格谈判的依据,从而对供应链整体利润进行重新分配,实现供应商和各零售商多赢。(5)研究了考虑供应商库存成本的库存路径问题。针对单供应商和多零售商组成的非一体化二级供应链,研究了在同时考虑供应商和零售商库存成本的前提下如何实现库存与配送联合优化,分别考虑了独立决策和联合决策情形下的库存和运输策略并构建了相应的求解算法。研究结果表明联合决策优于分散决策,能够节省大量的供应链成本。

【Abstract】 Since both inventory cost and transportation cost are important components of the supply chain cost, inventory control and distribution management are two significant fields in supply chain management. The high complexity of the real world problems increases the difficulty of solving inventory control and distribution management. Thus the traditional literature of company or supply chain operation usually takes them as two independent parts.Vendor managed inventory provides a new operation scheme for supply chain management. In this scheme, through advanced information technique, the supplier can acquire the inventory information of the retailers instantly and correctly, so that it can optimize the overall inventory of the supply chain system and decide the reasonable distribution plan from the system point. Based on vendor managed inventory, our dissertation discusses several familiar problems of the inventory and transportation integrated optimization. However, the literature usually focuses on the centralized supply chain, so that the theoretic research is difficult in applying to the practical supply chain operations. This dissertation considers of the noncentralized supply chain, mainly researches on the problems of inventory and transportation optimization based on vendor managed inventory. Here is the main research work of the dissertation.(1) It considers the optimal ordering strategy of inventory and transportation integrated optimization in a two-echelon decentralized supply chain consisting of one supplier and one retailer. It discusses three scenarios: decentralized decision, centralized decision and coordination decision based on price discount policy. Models and algorithms are proposed respectively. Numerical example shows that the price discount policy can increase the profits of both sides and implement the cooperation of the supplier and the retailer.(2) It considers the payment problem of transportation cost in the inventory and transportation integrated optimization. In a decentralized supply chain of one supplier and one retailer, three scenarios of inventory and transportation integrated optimization (ideal centralized supply chain, transportation cost paid by supplier and transportation cost paid by retailer) are discussed and modeled. Random numeric experiments prove that more supply chain profit can be obtained when the retailer pays transportation cost and the profit of supply chain is very close to the profit in ideal centralized supply chain. In order to attract the retailer to agree to pay transportation cost, profit division strategy is adopted to make sure both supplier and retailer obtain more profit.(3) It discusses the pricing problem of the inventory and transportation integrated problem under an elastic demand and sensitive price environment. Suppose the supplier is dominant in the supply chain, it considers pricing, inventory and transportation cost simultaneously under the price sensitive environment. It analyses non-cooperation decision and centralized decision models respectively. It designs two coordination strategies, revenue sharing and price discount, to appropriately divide the system profit to both parties to make sure of their cooperation. The experimental results show: comparing with the supplier-Stackelberg game structure, centralized cooperation decision can greatly increase the system profit. Through revenue sharing and price discount strategy, the system coordination can be implemented efficiently and the increased system profit can be appropriately divided to the retailer and the supplier.(4) It considers the inventory routing problem without considering the supplier’s inventory. In a two-echelon decentralized supply chain with one supplier and multi-retailers, it models the inventory and transportation integrated optimization problem, and proposes a modified nearest neighbor algorithm in order to increase the whole profit of supply chain by decreasing the transportation cost and inventory cost. It designs a proper pricing strategy, proposes the upper and lower bounds of the prices, reallocates the profit of the supply chain to the supplier and the retailers, thus realizes“multi-win”and improves supply chain coordination.(5) It considers the inventory routing problem considering the supplier’s inventory cost. In a two-echelon supply chain with one supplier and multi-retailers, the retailers and the supplier have inventory costs. It discusses how to implement the integrated optimization of inventory and transportation, analyses the decentralized and centralized decision scenarios respectively, builds the mathematical models and designs heuristic algorithms. The research results show that centralized decision is superior to decentralized decision, and can save a great deal of cost for the supply chain.

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