基于极大熵的单周期产品库存模型

研究具有自由需求分布的单周期问题。建立基本库存模型,给出期望利润表达式,运用极大熵准则确定需求的最可几分布,从而建立单周期产品库存模型,并得出最优订货批量。利用算例将该模型与Scarf订货规则和正态分布假设进行比较。结果表明,基于极大熵准则的库存模型能够获得更多的期望利润。     

基于提前期的多周期通用件库存模型

在单一周期库存模型的基础上，建立了多周期的通用件库存模型，对无通用件和有通用件的库存模型进行了比较研究，在模型中重点考虑提前期对通用件库存系统的影响，并以风神汽车有限公司有关数据进行了数据分析，揭示出基于提前期的单一周期模型中得出的结论并不能直接套用到多周期模型中，也就是说采用通用件并不总是能够降低库存水平和成本的，这个结论纠正了理论界认为单一周期库存模型的结论普遍适用的观点；研究基于提前期的通用件库存库存模型也是对通用件库存模型没有考虑提前期影响的一个扩展研究。     

多品种生产库存模型的几个问题

首先讨论了在一台设备上同时加工几种产品的同周期生产库存模型，并且给出了一个补充条件。其次，对于产品之间存在一定比例关系的情形，提出了一个生产库存的最优化模型。进一步还讨论了多品种库存的一般性模型。     

供应链环境下的供应商管理库存模型研究

基于文献[8]提出的供应商管理的订货和派送库存模型存在的参数设计过于复杂、储存成本计算有欠商榷的缺点,重新确定储存成本,并删除了对库存没有实质影响的部分参数,提出了既考虑顾客需要,又考虑供应商运输成本规模经济的固定周期检查派送和存货补足库存模型,给出了该模型的全局最优解计算,最后给出算例分析,并同经济定货模型进行比较。     

安全性第一准则下的组合贷款模型

提出了一种在概率准则意义下的组合贷款模型,并设计了基于随机模拟的混合优化算法进行求解。 该算法突破了各种贷款收益率必须服从正态分布的假定,可对贷款收益率是任意分布形式的模型进行求解。 经数值仿真,验证了算法的可行性。     

逆向拍卖采购下的库存与定价联合决策

研究单周期下零售商的联合采购与定价决策问题。在该问题中,零售商首先确定一个采购合同,然后供应商投标,通过逆向拍卖选取一个获胜的供应商进行采购,同时确定产品的零售价格,目标是最大化其期望利润。假定需求函数是乘式的,在一定的条件下,证明零售商的期望收益(不包括采购费用)是采购量的凹函数,从而得到其最优的采购与定价策略。特别对正态需求分布情形给出了零售商的采购量和利润函数的解析表达式,并进行数值计算与分析。结果表明参与拍卖的供应商数量越多或供应商对其边际生产成本的估价越分散对零售商越有利。     

有限修理能力下的可修件库存优化研究

针对传统可修件库存模型的假设与实际应用不符的问题,提出了一个基于有限修理能力的可修件库存模型,并且假设备件需求服从非稳态分布,分析了各种系统效能指标,并运用相关方法和排队理论进行了求解,最后结合实例进行了算法分析。结果表明,该模型既满足系统成本最低的要求,又实现了总短缺数最少的目标。     

不确定性激励下碰摩转子的振动响应识别

应用伪周期替代数据算法分析受不确定性激励的碰摩故障转子振动响应,对故障信号进行识别和分类。在考虑非线性油膜力及碰摩力作用的基础上,建立有界噪声激励作用下碰摩故障转子系统动力学模型,对系统振动响应信号及其相应替代数据进行对比分析与识别,应用关联维数作为检验假设的判别统计量,并结合Poincaré截面图、最大Lyapunov指数及分岔图进行验证。结果表明,替代数据算法能够有效识别此类受随机不确定激励转子系统的周期占优与混沌占优响应信号,可进一步应用于受不确定性激励转子系统的信号识别与故障诊断研究。     

通用电机产品族协同设计的模糊优化

产品族设计是大规模定制中的核心内容,许多文献在假定产品特征确定情况下,采用平台参数和非平台参数,提出了大规模定制下的产品族设计优化方法。基于产品族设计理念,针对含有不确定特征的产品族设计中的一种基本类型——产品参数与产品功能之间的映射含有模糊系数的情形,建立一种对平台参数和非平台参数进行协同优化的模糊双层线性规划模型,利用有关模糊算法对模糊条件下的通用电机产品族协同设计进行优化。     

随机批量运输的柔性作业车间AGV配置优化

针对柔性作业车间中物料搬运系统的AGV数量配置问题,以最小化AGV购置成本为目标,建立具有系统产出率和生产周期双重约束的优化模型。由于该优化问题是一个随机非线性的整数规划问题,且约束条件无法用决策变量的封闭形式表示,为此,提出一种基于仿真的粒子群优化算法求解该问题。针对具有随机批量运输特征的柔性作业车间,基于离散事件仿真平台构建系统的性能估算模型,提出一种嵌入仿真模型的粒子群优化算法求解AGV数量配置的优化方案。通过仿真算例实验以及不同优化方法对比,对比结果显示,该方法较其他算法在优化结果的优越性和稳定性上分别平均提高了8%和8.9%。分析实际应用案例确定了优化的配置方案,结果验证了所提方法的有效性,具有实际应用价值。     

电力物资复合泊松需求下的最优订货量

以上海电力公司的物资供应体系为背景,给出了（T,Q）库存策略下服从复合泊松分布的电力物资最优订货量的算法。建立复合泊松分布下的库存成本模型,对此模型用闭式算法求得其最小库存成本下的最优订货量,将该算法应用于电力物资进行实证分析。数值结果表明,与传统的报童模型相比,本文提出的最优订货量算法更适用于间断需求。     

基于设备使用周期的备件库存控制模型研究

由于设备系统的复杂性、设备故障的随机性,备件的需求难以准确确定,相关费用也难以做出准确评估,从而使得备件这一类库存控制问题变得相当复杂.基于备件的需求量与设备使用周期密切相关这一关键点,从设备的整个使用周期入手,结合设备的使用情况,在备件需求率随时间变化的情况下,对备件库存控制问题进行了研究,建立了在设备整个使用周期内使备件总订货成本和存储费用最低的数学模型,给出了备件最佳订货次数、订货时间和订货批量的计算公式.最后给出了一个算例以证明模型的实用性.     

DEALER INVENTORY MANAGEMENT SYSTEMS

This paper presents a model for analyzing inventory control policies for dealers that support the sales and service of manufactured goods. The environment faced by dealers is characterized by multiple stochastic demand classes (prioritized into emergency and regular), a principal source for boui emergency and regular requirements, multiple secondary sources for expedite requirements, and constraints on the lead time and service performance. We are concerned, in particular, with how dealers manage their inventory stockpiles and select expedite sources for replenishment when they have the option of prioritizing customers. The analysis is based on a periodic review, stochastic demand, (s,S) inventory model of dealer stock control. Exact Markov processes and approximate renewal based models are derived based on Cohen, Kleindorfer and Lee [4] and Cohen and Lee [5]. An approximation is used to develop a heuristic algorithm. Extensive numerical testing indicates that the algorithm generates solutions with acceptable cost and service penalties.     

Capacitated disassembly scheduling with random demand

This paper considers disassembly scheduling, which is the problem of determining the quantity and timing of the end-of-use/life products to be disassembled while satisfying the demand for their parts obtained from disassembling the products over a planning horizon. This paper focuses on the problem with stochastic demand of parts/modules, capacity restrictions on disassembly resources, and multiple product types with a two-level product structure. The two-level product structure implies that an end-of-use/life product is hierarchically decomposed into two levels where the first level corresponds to the parts/modules and the second level corresponds to the product. We formulate the problem as a stochastic inventory model and to solve the problem we propose a Lagrangian heuristic algorithm as well as an optimisation algorithm for the sub-problems obtained from Lagrangian decomposition. The test results on randomly generated problems show that the Lagrangian heuristic algorithm demonstrates good performance in terms of solution quality and time.     

基于供需一体化协同控制的供应链库存模型

根据供需一体化协同库存控制策略，构建了一个一体化库存模型。在模型里，假定提前期需求是随机的且服从正态分布，允许在提前期内发生缺货，并产生缺货成本；假定提前期是可控的，能够通过增加成本缩短提前期。该模型通过同时计算最优订货量、再订货点、提前期以及运送批次．使供需一体化库存总成本最小。实例分析证明该模型能够达到节约成本的目的。     

An EOQ model when production standards are assumed to be normally distributed

In this paper an EOQ model is developed especially for a production environment where the inventory to be controlled is raw material. The fundamental difference between this model and others is that a stochastic demand is placed upon the inventory in terms of the time for an individual to consume one unit of inventory rather than the number of units consumed in some time interval. A shortage cost for inventory is imposed via the idle machine (man) cost. The optimal re-order quantity is determined as a function of the stockout probability and the optimal stockout probability is obtained via a one-dimensional search, over some prescribed set of feasible stockout probabilities.     

经济订货批量研究

以企业生产物流中的库存管理为切入点,通过批量折扣的双箱系统模型,定量地分析了需求的再订购批量和折扣批量之间的关系。指出了JIT的局限性,并且简要地介绍了新型的库存管理方法一VMI(供应商管理用户库存),同时提出了一些见解。     

Inventory lot-sizing with supplier selection under non-stationary stochastic demand

Inventory lot-sizing and supplier selection problem has been studied in the literature considering mainly time-varying deterministic demand. However, in real life, most of the products exhibit non-stationary stochastic demand. In this context, we propose an integer linear programming model for inventory lot-sizing and supplier selection problem under non-stationary stochastic demand with all-units quantity discounts and fill rate constraints. Through detailed analysis of experimental results, we show the impacts of fill rate requirements and demand coefficient of variation on costs, inventory levels and order allocations.     

A stochastic inventory model for an immediate liquidation and price-promotion decision under price-dependent demand

We consider a periodic review stochastic inventory system where the current on-hand inventory exceeds the maximum supply needs in the future. Consequently, one must make an immediate inventory liquidation decision on the liquidation quantity and promotional price with the goal of maximising the overall profit where the demand during the liquidation period (DDLP) is a random variable whose distribution depends on the promotional price. We develop a price-dependent DDLP model and an inventory model for optimising the liquidation quantity and unit promotional price. The model is applicable for general distributions of the DDLP and regular demand (i.e. demand during the future periods following the promotion period). We also investigate four special cases where the DDLP and regular demand are assumed to be either exponential or uniform random variables. The two models that assume the exponential distribution for regular demand can be examined analytically and simplified using the mathematical properties we derive. The additional two models that assume the uniform distribution for regular demand do not have closed-form expressions but can be solved numerically. Some numerical examples are presented for further elaboration of the models and to demonstrate their practical use.     

考虑血型替代策略的紧缺血液采集优化

为了保障临床用血需求,研究紧缺血液的采集优化问题。在血液供给严重短缺的情况下,血型替代是一种重要的应急策略,由此对紧缺血液采集决策产生重要影响。以血液中心-医院两级库存系统为对象,在分析血型替代策略对血液库存控制影响的基础上,考虑随机需求等因素,建立了一个带服务水平约束的系统期望总成本最小的紧缺血液采集优化模型,包含血液中心和医院的血液库存成本,以及血型替代、血液最优采集量短缺和医院缺血产生的惩罚成本。采用离散非线性混合整数规划对模型进行描述。并针对模型特点,设计了一种精确算法。算例结果表明考虑血型替代策略,系统期望总成本下降74.67%。因而考虑血型替代策略的血液采集优化决策能有效缓解血液紧缺问题、提高紧缺血液保障能力。