一类多对多物流系统的运送频率选择优化问题研究

多供应商多客户物流系统的周期运送库存决策问题是一个非常复杂的问题,但它在供应链管理中又极其重要.本文主要考虑一个由多个供应商、一个联运中心和多个客户组成的三级物流系统的运送频率选择优化问题.假定两级库存均采用周期补货策略,且补货周期满足二次幂(POT)策略,每个客户处的产品需求为确定性需求.假设给定一套可行频率的情况下,选择使整个系统总的长期平均成本最小化的联运中心的补货策略和联运中心到各客户的配送策略.分为单频率配送和多频率配送两种情况分别建立了数学模型,并设计了相应的近似算法——基于支配性的邻域搜索启发式算法和基于饱和性的邻域搜索启发式算法.计算试验显示,本文所设计的近似算法对于求解多对多配送这样的大型组合优化问题是有效的.     

基于CRE的供应链渠道协作利润优化研究

为了实现供应链合作伙伴的双赢和多赢,在由一个制造商和两个批发商组成的供应链中,以制定最优共同补货周期策略为核心,制造商作为盟主指定共同补货周期和折扣率,批发商作为成员企业按共同补货同期的整数倍进行补货.制造商采用一致价格折扣的方式弥补批发商成本的增加.考虑到需求的可变性和是否实行共同补货周期策略,建立了制造商、批发商和整个供应链系统的利润优化模型并进行了模拟.结果表明共同补货周期策略可以实现多方收益的帕累托改进,供应链三方协作追求整体收益,可以实现"共赢".     

带短期价格折扣和允许两次特殊补货的库存决策模型

针对供应商提供短期价格折扣且允许零售商两次特殊补货的库存系统, 建立了以零售商库存效益最大化为目标的库存决策模型, 分析了模型的性质, 根据经济订单批量补货决策下补货时间点与折扣时段的关系, 确定了零售商在不同补货策略下的库存效益增值函数. 据此给出零售商相应的最优补货策略函数表达式, 提出了该模型的一个全局优化算法, 并通过数值算例验证了模型和算法的有效性与可行性.     

VMI条件下具有复合二项随机需求的销售商库存策略研究

考虑一个典型的单一产品的二级供应链系统:单供应商对单销售商,假定系统中销售商的需求分布为复合二项分布,未满足的需求机会损失;补货间隔时间为一随机变量.本文采用概率方法对销售商的需求分布、期望缺货、期望库存周期及库存的稳定性分布进行研究的基础上,构建了使单位时间内销售商的期望库存成本费用最小的库存模型,由此模型便可确定VMI模式下供应商对销售商的库存补货参数s和S,并且给出了在补货响应时间为泊松分布的情况下模型的求解算法,还给出了及时补货响应情况下的5个算例.为补货策略的实施提供了一种简单易于控制的思路和方法.     

基于前摄性调度的电动汽车路径问题研究

针对车辆调度过程中资源不均衡的问题,利用需求的不确定性,将配送周期划分为初始配送阶段和补货阶段,建立多阶段电动汽车的两级车辆路径优化模型.根据需求的动态程度对配送区域进行划分,结合前摄性调度和反应性调度策略,提出了一种混合禁忌搜索算法(HTSA)来求解该模型.在真实的案例和多个基准评估算例上的实验结果表明:模型和算法的性能优于传统的启发式算法,具有一定的实用价值.     

基于AGV的智能仓库系统储位分配问题研究

研究了基于自动引导机器人(AGV)的"货到人"拣选模式下的智能仓库系统补货阶段的储位分配问题.根据待拣选订单信息计算出商品之间的关联度,考虑了货架上存放的物品信息、空余储位数量、待补货物品信息,以同一货架上的各种商品之间的关联度之和最大化为目标函数,建立了补货阶段储位分配问题的整数规划模型;设计了求解模型的贪婪算法,并分析了算法复杂度.利用一个具体实例进行模拟计算,分析了贪婪算法的求解效果.进一步利用不同规模算例进行模拟计算,分析了贪婪算法的计算时间和近似比,结果显示贪婪算法可以在很短的时间内得到近似最优解,近似比不超过1.15.设计的贪婪算法可以作为智能仓库管理信息系统的核心算法.     

允许缺货且带数量折扣的腐烂物质库存模型

在短缺量拖后率是等待时间的负指数函数、订购成本是批量的线性函数的条件下,建立了带数量折扣的腐烂物质库存模型,目标是优化总平均利润.在给定销售价格的情况下,证明了库存系统的最优补货策略存在且唯一;且若采用最优补货策略,平均利润函数是销售价格的凹函数;最后给出了模型的算法,并用数值例子说明了模型和算法的有效性.     

需求率为斜坡型的一类变质性物品最优库存策略

本文在考虑需求率服从斜坡型分布的情况下,研究了允许缺货且缺货完全回补、变质率服从威布尔分布、补货率为无穷、有限计划期内的库存模型,证明了最优补货策略的存在性,并给出了求解最优补货策略的算法.     

一类梯形需求且允许缺货的两货栈库存系统的最优补货策略

已有关于梯形需求的产品库存问题多集中在单一货栈的框架内讨论,而这一需求类型的两货栈问题还鲜有被研究.对此,在允许缺货的条件下,考虑租用货栈以及拖后延迟补货的情况,建立了以系统平均成本最小为目标的两货栈库存模型,从而将现有基于梯形需求的库存问题作了进一步扩展.然后分析了此类库存系统最优策略的存在性和唯一性,并提供了求解模型的算法,最后用数值例子和敏感性分析对所建模型进行了说明.     

基于改进蚁群算法的无人仓的多AGV避碰路径优化策略

对无人仓库中多AGV系统的避碰路径优化问题进行了研究,提出了一种基于弹性时间窗和改进蚁群算法的多AGV避碰路径优化策略.通过对传统蚁群算法改进启发式信息和信息素更新策略,来提高算法的执行速度和寻优能力,提出AGV任务优先级排序并改进冲突解决策略来解决多AGV之间的不同路径冲突.基于电商物流无人仓库的环境,利用MATLAB仿真软件对多AGV避碰路径规划进行建模分析.实验结果表明,基于弹性时间窗和改进蚁群算法的可以实现多AGV避碰路径规划,并能够短时间内找到避碰最优路径.     

Evaluation of three production planning procedures for the use of recipe flexibility

Process industries often obtain their raw materials from mining or agricultural industries. These raw materials usually have variations in quality, which often lead to variations in the recipes used for manufacturing a product. Another reason for varying the recipe is to minimize production costs by using the cheapest materials that still lead to a satisfactory quality in the product. A third reason for using recipe flexibility is that it may occur that at the time of production not all materials for the standard recipe are available. In earlier research we showed under what conditions the use of this type of recipe flexibility should be preferred to the use of high materials stock to avoid materials shortages. We also showed that the use of recipe flexibility to account for material shortages can be justified if the material replenishment leadtime is long, the demand uncertainty is high and the required service level is high. In this paper we assume that these conditions are satisfied and we investigate three different production planning procedures that make use of recipe flexibility to cope with the uncertainty in demand and supply. We assume that the customer order leadtime is much smaller than the material replenishment leadtime, and therefore demand uncertainty is high. The optimal procedure optimizes material use over a planning horizon equal to the material replenishment leadtime, taking into account the customers orders and knowledge of the distribution function of future demand. The deterministic procedure also optimizes the material use over the material replenishment leadtime, but it assumes a deterministic demand level for unknown orders. The simplest, myopic procedure optimizes material use over only the accepted customer orders. These three procedures are investigated via an experimental design of computer simulations of an elementary small scale model of the production planning situation. The results show that the optimal procedure outperforms the other two procedures. Furthermore, for a realistic cost structure in feed industry under certain circumstances the use of the optimal procedure may lead to a 4% increase in profit. However, this improvement must be weighted against the cost incurred by the operational use of this complex procedure. Based on these considerations and the numerical results in this paper, we may expect that for some situations in practice the use of the simplest myopic procedure, optimizing material use only over the available customer orders, will be justified from an overall cost point of view.     

考虑顾客退货和固定成本的联合补货与定价策略

为了吸引更多顾客,许多电子商务零售商允许顾客在一定时间内退货,导致其利润明显减少。同时,在补货时不仅产生依赖补货量的变动成本,而且会产生与补货量无关的固定成本。基于此,以最大化电子商务零售商的利润为目标,建立考虑顾客退货和固定成本的联合补货与定价模型,其中顾客的退货量与满足的需求呈正比。在一般需求情形下,部分刻画多期问题的最优策略;在特殊需求情形下,证明(s,S,p)策略对单期问题最优,并对多期问题的最优策略进行严格刻画。根据已有刻画为多期问题构造启发式策略。数值结果表明启发式策略近似最优;当初始库存水平足够高/低时,最优补货水平和定价随退货率与固定成本单调变化。关键词:联合补货与定价模型;顾客退货;固定成本;随机动态规划;最优策略     

Modeling customer impatience in a newsboy problem with time-sensitive shortages

Customers across all stages of the supply chain often respond negatively to inventory shortages. One approach to modeling customer responses to shortages in the inventory control literature is time-dependent partial backlogging. Partial backlogging refers to the case in which a customer will backorder shortages with some probability, or will otherwise solicit the supplier’s competitors to fulfill outstanding shortages. If the backorder rate (i.e., the probability that a customer elects to backorder shortages) is assumed to be dependent on the supplier’s backorder replenishment lead-time, then shortages are said to be represented as time-dependent partial backlogging. This paper explores various backorder rate functions in a single period stochastic inventory problem in an effort to characterize a diversity of customer responses to shortages. We use concepts from utility theory to formally classify customers in terms of their willingness to wait for the supplier to replenish shortages. Under mild assumptions, we verify the existence of a unique optimal solution that corresponds to each customer type. Sensitivity analysis experiments are conducted in order to compare the optimal actions associated with each customer type under a variety of conditions. Additionally, we introduce the notion of expected value of customer patience information (EVCPI), and then conduct additional sensitivity analyses to determine the most and least opportune conditions for distinguishing between customer behaviors.     

Expulsion and scheduling control for multiclass queues with heterogeneous servers

We consider an M/M/2 system with nonidentical servers and multiple classes of customers. Each customer class has its own reward rate and holding cost. We may assign priorities so that high priority customers may preempt lower priority customers on the servers. We give two models for which the optimal admission and scheduling policy for maximizing expected discounted profit is determined by a threshold structure on the number of customers of each type in the system. Surprisingly, the optimal thresholds do not depend on the specific numerical values of the reward rates and holding costs, making them relatively easy to determine in practice. Our results also hold when there is a finite buffer and when customers have independent random deadlines for service completion.     

Retailer’s optimal replenishment and payment policies in the EPQ model under cash discount and two-level trade credit policy

The main purpose of this paper is to investigate the retailer’s optimal cycle time and optimal payment time under the supplier’s cash discount and trade credit policy within the economic production quantity (EPQ) framework. In this paper, we assume that the retailer will provide a full trade credit to his/her good credit customers and request his/her bad credit customers pay for the items as soon as receiving them. Under this assumption, we model the retailer’s inventory system as a cost minimization problem to determine the retailer’s optimal inventory cycle time and optimal payment time under the replenishment rate is finite. Then, an algorithm is established to obtain the optimal strategy. Finally, numerical examples are given to illustrate the theoretical results and obtain some managerial phenomena.     

A Dynamic Distribution Model with Warehouse and Customer Replenishment Requirements

This paper addresses a multiperiod integrated model that plans deliveries to customers based upon inventories (at warehouse and customer locations) and vehicle routes. The model determines replenishment quantities and intervals at the warehouse, and distribution lots and delivery routes at customer locations. We investigate coordination of customer and warehouse replenishment decisions and illustrate their interdependence. Computational experience on randomly generated problems is reported. We show that ordering policy at the warehouse is a function of how goods are distributed to lower echelons and that coordination leads to cost reduction.     

Equilibrium and optimal behavior of customers in Markovian queues with multiple working vacations

This paper studies the customers’ equilibrium and socially optimal joining–balking behavior in single-server Markovian queues with multiple working vacations. Different from the classical vacation policies, the server does not completely stop service but maintains a low service rate in vacation state in case there are customer arrivals. Based on different precision levels of the system information, we discuss the observable queues, the partially observable queues, and the unobservable queues, respectively. For each type of queues, we get both the customers’ equilibrium and socially optimal joining–balking strategies and make numerical comparisons between them. We numerically observe that their equilibrium strategy is unique, and especially, the customers’ equilibrium joining probability in vacation state is not necessarily smaller than that in busy state in the partially observable queues. Moreover, we also find that the customers’ individual behavior always deviates from the social expectation and makes the system more congested.     

Improved approximation for the capacitated inventory access point problem

The Inventory Access Point (IAP) is the single-item lot-sizing problem where a single customer faces demands in a discrete planning horizon, and the goal is to find a replenishment policy that minimizes the total inventory and ordering costs. While the uncapacitated version is polynomial, only a 3-approximation is known for the capacitated case. We improve this factor to 2.619 and, as a byproduct, we also improve the best factor for SIRPFL, which is a variant with multiple depots and customers.