供应商管理库存中的一种供需问题及优化模型

在供应商管理库存(VMI)的条件下,当供应商为不同区域的零售商供应同种商品时,为了降低供应商的供应成本,根据各零售商未来T期的需求,建立了以总成本最小为目标的供应商协调供应模型,并分别用启发式算法和遗传算法求解该模型。通过算例表明,相对于单纯以按时按量满足各零售商的需求为目标的供应方案,这两种方法得到的方案总成本均大大降低,而且遗传算法的解要优于启发式算法的解。     

Developing economic order quantity model for non-instantaneous deteriorating items in vendor-managed inventory (VMI) system

This paper develops an economic order quantity model for non-instantaneous deteriorating items with and without shortages to investigate the performance of the vendor-managed inventory (VMI) system. This model is developed for a two-level supply chain consisting of a single supplier and single retailer with a single non-instantaneous deteriorating item. A numerical example and sensitivity analysis are provided to illustrate how increasing or reducing the related parameters change the optimal values of the decision variables of the two proposed models. The results show that VMI works better and charges lower cost in all conditions.     

考虑多类零售商的库存与运输VMI 集成策略

研究由单批发商多零售商构成的供应商管理库存(VMI)供应链,批发商向外部供应商订货,并为价格和缺货成本不同的零售商补货.首先构造解析模型以分析如何为多类零售商确定不同的库存分配策略;然后将这一最优的库存分配策略与最优的先到先服务(FCFS)策略进行比较,同时比较相应简化的库存分配策略和简化的FCFS策略.解析和算例结果表明,简化的库存分配策略总是优于简化的FCFS策略,而最优的库存分配策略大部分情况下优于最优的FCFS策略.     

基于混合需求的供应链多级库存协同订货模型

针对供应链多级库存系统存在混合需求的情况,建立了基于混合需求的多级库存协同订货模型。该模型假设在供应链中只有最下游节点面临的需求是独立需求,而其他上游节点面临的需求都是与之相关的相关需求。由于相关需求是一种块状需求,其库存成本构成与独立需求明显不同。因此,通过对多级库存系统的库存成本构成进行重新分析,分别给出了需求确定时不允许缺货和允许缺货的协同订货模型。另外,还通过对安全库存的分析给出了需求不确定时的协同订货模型。最后,给出了模型求解的遗传算法,并进行了实例仿真分析,展示了这种协同订货模型在混合需求的供应链中的实用性。     

Optimization of vendor-managed inventory systems in a rolling horizon framework

This paper aims at designing a dynamic VMI system. In this system, the entire supply chain performance is optimized in terms of production planning at vendor’s site, distribution strategy, and inventory management at manufacturer’s site. We also explore some of the complications involved in setting up such a system. The VMI system is modeled as a mixed-integer linear program (MILP) using discrete-time representation. The mathematical representation follows the resource-task network (RTN) formulation. To address the complexity of the problem, different optimization-based solution algorithms are proposed and compared in terms of solution quality and CPU time. First, the problem is solved directly using an exact detailed model. Secondly, an iterative procedure combines a novel aggregate model with the detailed model to provide aggregate pre-matches for the detailed binary variables. Finally, a novel rolling horizon approach that simultaneously combines the aggregate and the detailed models is designed to solve the problem. The entire VMI system is tested with an illustrative example.     

A tabu search procedure for coordinating production,inventory and distribution routing problems

This paper addresses the problem of optimally coordinating a production‐distribution system over a multi‐period finite horizon, where a facility production produces several items that are distributed to a set of customers by a fleet of homogeneous vehicles. The demand for each item at each customer is known over the horizon. The production planning determines how much to produce of each item in every period, while the distribution planning defines when customers should be visited, the amount of each item that should be delivered to customers and the vehicle routes. The objective is to minimize the sum of production and inventory costs at the facility, inventory costs at the customers and distribution costs. We also consider a related problem of inventory routing, where a supplier receives or produces known quantities of items in each period and has to solve the distribution problem. We propose a tabu search procedure for solving such problems, and this approach is compared with vendor managed policies proposed in the literature, in which the facility knows the inventory levels of the customers and determines the replenishment policies.     

水产品供应商管理库存(VMI)模型的设计

供应商管理库存VMI（vendor managed inventory）技术是供应链管理理论出现以后提出来的一种新的库存管理模式，其主要目的是将供应链上的整体存货水平降到置低限度。结合水产品及其库存管理的特点，本文分析了水产品供应商管理库存（VMI）的基本特征，在此基础上构建了一个适用于水产品的VMI模型。     

Coordination-based inventory management for deteriorating items in a two-echelon supply chain with profit sharing

This study develops a model for inventory management consisting of a two-echelon supply chain (SC) with profit sharing and deteriorating items. The retailer and the supplier act as the leader and follower, in which the supplier faces a huge setup cost and economic order quantity ordering strategy. The market demand is affected by the sale price of the product, and the inventory has a deterioration rate following a Weibull distribution. The retailer executes three profit-sharing mechanisms to motivate the supplier to participate in SC optimisation and to extend the life cycle of the product. A search algorithm is developed to determine the solutions as using the profit-sharing mechanisms. The outcomes from numerical experiments demonstrate the profitability of the proposed model.     

基于库存切换的不确定动态供应链网络系统模糊鲁棒控制

研究基于库存切换的不确定动态供应链网络系统的鲁棒运作问题.首先,建立含有系统参数不确定和顾客需求不确定的动态供应链网络的离散T-S模糊模型;然后,提出一种新的模糊鲁棒控制策略,该控制策略不仅可以有效遏制子系统切换时产生的较大波动,而且可以抑制不确定因素对供应链网络的影响,进而保证供应链网络在不确定环境下鲁棒稳定;最后,通过仿真实例表明了所提出模糊鲁棒控制策略的有效性.     

基于颜色Petri网的不确定库存模型性能仿真

供应链中由于信息传递过程中出现的信息膨胀引起牛鞭效应造成各种成本的急剧增长,为使目标函数费用最小,基于颜色Petri网建立了不同需求预测方法及库存策略的CPN模型。在订单数量等变量随机产生以及订货点等因素不确定的情况下,通过实验仿真数据确定了存储、订货及缺货费用与各种不确定变量的关系,从而确定了最优的库存策略。通过对比实验证明了该方法的有效性及正确性。     

基于盘点机的生产现场数据采集及处理系统

针对生产现场基础数据的采集、传递、（预）处理操作,提出了基于盘点机的自动识别、处理方法。首先,基于各部门间对基础数据处理过程的需求分析,构建了系统实施框架,并以条形码为标识,进行信息编码设计。其次,划分了系统的各功能模块,并进行了详细流程分析,在此基础上,采用HTBase语言在盘点机上开发了数据采集及处理系统。实现了在生产现场通过盘点机对成品的采集、组码、修改、查询、确认及传递等功能,为企业资源管理系统提供实时、准确、可靠数据。     

Deterministic inventory model for recycling system

An important new trend in supply chain management is repair, remanufacturing, recycling, or reuse of products collected from the end user after they have reached the end of their useful life. This paper deals with inventory control for a recycling system. For the system, we assume that demand is deterministic, and a fixed fraction of demands is returned and used as raw material of new products. We propose inventory policies and present procedures for determining the optimal policy parameters. Received: May 2005 / Accepted: December 2005     

An effective heuristic for solving a combined cargo and inventory routing problem in tramp shipping

In this paper a vendor managed inventory (VMI) service in tramp shipping is considered. VMI takes advantage of introducing flexibility in delivery time and cargo quantities by transferring inventory management and ordering responsibilities to the vendor which in this case is a shipping company. A two-phase heuristic is proposed to determine routes and schedules for the shipping company. The heuristic first converts inventories into cargoes, thus turning the problem into a classic ship routing and scheduling problem. It then uses adaptive large neighborhood search to solve the resulting cargo routing and scheduling problem. The heuristic iteratively changes the cargoes generated to handle the customer’s inventories, based on the information obtained from an initial solution. Computational results are presented, discussed and compared with exact solutions on large realistic instances. The results reveal the potential savings from converting traditional contracts of affreightment to an integrated VMI service. The factors that influence the benefits obtainable through VMI are also analyzed.     

模糊需求下物流系统CLRIP 问题研究

从物流系统集成的角度出发．考虑到客户需求的模糊性，建立了多仓库单级物流配送系统中的设施选址、车辆运输路线安排、库存控制的集成优化模型．用来解决在给定的多个潜在设施点中选出一系列设施的位置．并确定巡回运输路线．同时基于客户所采用的单时期模糊需求存贮策略确定其最佳订货量，并给出了求解该模型的启发式算法．最后通过实例计算证明了上述模型和算法的有效性．     

Optimal inventory control policy and supply chain coordination problem with carbon footprint constraints

Carbon footprint constraints exert pressure on supply chains to reexamine decisions. In this paper, we consider carbon transfer cost and carbon holding cost in a supply chain. A multiperiod dynamic programming model with carbon footprint constraints is presented to investigate the impact of carbon transfer cost and carbon holding cost on inventory control policy as well as the supply chain coordination problem. A two‐control limit inventory control policy is proved to be optimal and a contract with wholesale price, subsidy, and fixed setup cost is verified analytically to coordinate the supply chain. Finally, a numerical study is conducted to reveal managerial insights. We find that when the supply chain is coordinated, the chain's profit is more sensitive to carbon transfer cost while inventory level is more sensitive to carbon holding cost. Additionally, because of the complexity of the coordinated contract, when it is not easy to coordinate the supply chain, it is better to keep the values of wholesale price, subsidy, and fixed setup cost below the corresponding values for the coordinated supply chain.     

随机需求下双渠道供应链库存动态交互优化

针对双渠道供应链库存系统导致的缺货与库存积压等问题，在线上线下均为随机需求的条件下，考虑生产延迟和物流延迟，建立了双渠道库存的单独控制、集中控制和交叉补货控制这三种模式的动态优化模型。首先，以库存动态微分方程为基础，创新性地以控制理论为指导思想，以泰勒展开和拉普拉斯变换为手段，得到双渠道库存系统的反馈传递函数；其次，考虑了交叉补货的进销存过程中的周期间交互、上下游间交互以及渠道间交互，利用延迟控制、反馈控制和比例-积分-微分（PID）控制构造了双输入、双输出的复杂交互系统，以此寻求双渠道库存系统自身以及渠道间的动态供需双平衡，优化双渠道库存持有量，降低缺货次数和缺货量并使其保持动态稳定状态；最后，通过数值仿真实验，对比三种双渠道库存控制策略。仿真结果表明，在线上线下渠道为不同分布的随机需求时，交叉补货控制的剩余库存比独立库存控制降低了4.9%，交叉补货控制的缺货率与独立控制和集中控制相比分别下降了66.7%和60%。实验结果表明，在线上线下渠道为不同分布的随机需求的情况下使用双渠道交叉补货策略能很好地降低库存持有量，减少缺货次数和缺货量，从而节约库存成本。     

随机需求下双渠道供应链库存动态交互优化

针对双渠道供应链库存系统导致的缺货与库存积压等问题,在线上线下均为随机需求的条件下,考虑生产延迟和物流延迟,建立了双渠道库存的单独控制、集中控制和交叉补货控制这三种模式的动态优化模型。首先,以库存动态微分方程为基础,创新性地以控制理论为指导思想,以泰勒展开和拉普拉斯变换为手段,得到双渠道库存系统的反馈传递函数;其次,考虑了交叉补货的进销存过程中的周期间交互、上下游间交互以及渠道间交互,利用延迟控制、反馈控制和比例-积分-微分（PID）控制构造了双输入、双输出的复杂交互系统,以此寻求双渠道库存系统自身以及渠道间的动态供需双平衡,优化双渠道库存持有量,降低缺货次数和缺货量并使其保持动态稳定状态;最后,通过数值仿真实验,对比三种双渠道库存控制策略。仿真结果表明,在线上线下渠道为不同分布的随机需求时,交叉补货控制的剩余库存比独立库存控制降低了4.9%,交叉补货控制的缺货率与独立控制和集中控制相比分别下降了66.7%和60%。实验结果表明,在线上线下渠道为不同分布的随机需求的情况下使用双渠道交叉补货策略能很好地降低库存持有量,减少缺货次数和缺货量,从而节约库存成本。     

供应商具备多级生产率的供应链控制策略仿真

研究供应商具有多级生产率的供应链库存成本控制策略问题。在满足客户与销售商随机性订单需求的基础上,以供应链的整体运营成本最低为目标,运用Arena仿真平台对由供应商、销售商、客户构成的多级供应链库存系统进行了建模和仿真优化,制定合理的销售商的库存策略以及供应商的生产库存策略。为具备多级生产率的供应链系统控制策略提供了一种更科学合理的决策方法,对以后的类似研究具有一定的借鉴意义。     

Asynchronous action-reward learning for nonstationary serial supply chain inventory control

Action-reward learning is a reinforcement learning method. In this machine learning approach, an agent interacts with non-deterministic control domain. The agent selects actions at decision epochs and the control domain gives rise to rewards with which the performance measures of the actions are updated. The objective of the agent is to select the future best actions based on the updated performance measures. In this paper, we develop an asynchronous action-reward learning model which updates the performance measures of actions faster than conventional action-reward learning. This learning model is suitable to apply to nonstationary control domain where the rewards for actions vary over time. Based on the asynchronous action-reward learning, two situation reactive inventory control models (centralized and decentralized models) are proposed for a two-stage serial supply chain with nonstationary customer demand. A simulation based experiment was performed to evaluate the performance of the proposed two models. Chang Ouk Kim received his Ph.D. in industrial engineering from Purdue University in 1996 and his B.S. and M.S. degrees from Korea University, Republic of Korea in 1988 and 1990, respectively. From 1998--2001, he was an assistant professor in the Department of Industrial Systems Engineering at Myongji University, Republic of Korea. In 2002, he joined the Department of Information and Industrial Engineering at Yonsei University, Republic of Korea and is now an associate professor. He has published more than 30 articles at international journals. He is currently working on applications of artificial intelligence and adaptive control theory in supply chain management, RFID based logistics information system design, and advanced process control in semiconductor manufacturing. Ick-Hyun Kwon is a postdoctoral researcher in the Department of Civil and Environmental Engineering at University of Illinois at Urbana-Champaign. Previous to this position, Dr. Kwon was a research assistant professor in the Research Institute for Information and Communication Technology at Korea University, Seoul, Republic of Korea. He received his B.S., M.S., and Ph.D. degrees in Industrial Engineering from Korea University, in 1998, 2000, and 2006, respectively. His current research interests are supply chain management, inventory control, production planning and scheduling. Jun-Geol Baek is an assistant professor in the Department of Business Administration at Kwangwoon University, Seoul, Korea. He received his B.S., M.S., and Ph.D. degrees in Industrial Engineering from Korea University, Seoul, Korea, in 1993, 1995, and 2001 respectively. From March 2002 to February 2007, he was an assistant professor in the Department of Industrial Systems Engineering at Induk Institute of Technology, Seoul, Korea. His research interests include machine learning, data mining, intelligent machine diagnosis, and ubiquitous logistics information systems. An erratum to this article can be found at     

An integrated production and inventory model for a system comprising an assembly supply chain and a distribution network

This study investigates the production and inventory problem for a system comprising an assembly supply chain and a distribution network. A uniform lot size is produced uninterruptedly with a single setup at each production stage. Equal-sized batch shipment policy is applied to the whole system and the number of batches can be varied. All retailers have agreed on a joint replenishment policy with a common replenishment cycle. The objective is to determine the optimal common replenishment cycle, the number of batches of each production stage and retailer, all of which minimises the integrated total cost. Moreover, a new concept is introduced; namely, critical replenishment cycle. The replenishment cycle division (RCD) and recursive tightening (RT) methods are then developed to obtain the optimal solutions to the subject problem. Two theorems are verified to ensure the solutions obtained by the RCD and RT methods reaching the global optimum. An example is presented to illustrate the procedures involved in the RCD and RT methods.