基于PI的企业动态库存补货模型与算法

PI(physical internet)环境下的物流网络具有互联、开放和共享的特点,缺货的PI-枢纽或零售商可根据货源选择策略动态选择为其补货的供应商或PI-枢纽。为解决PI环境下库存补货问题,提出了IB-EB(installation-echelon)混合补货策略。以最小化库存补货成本为目标,补货量和再订购点为决策变量,构建了PI环境下的动态库存补货模型。针对该混合整数非线性规划模型,应用粒子群优化算法求解出多个补货预案,再将其带入仿真环境循环优化求解。最后,以中国航空器材进出口公司为例,验证了模型可解性及算法的可行性。结果表明PI环境下货源策略的选择对库存补货成本和补货策略具有十分重要的影响,为企业在不同补货条件下选择货源提供了参考依据。     

基于时变需求的一对一供应链库存决策研究

随着竞争日趋激烈,需求变化节奏加快,需求时变性越加明显.在需求时变的环境下探讨了等周期补货情形下缺货时点优化以及非等周期补货情形下缺货时点与补货时点优化问题,特别着重研究了补货时点局部优化与整体优化的决策模型,并对非等周期补货与等周期补货、补货时点整体优化与补货时点局部优化作对比分析,并发现,在时变需求环境下非等周期补货与补货时点整体优化在降低库存成本方面具有明显优势.同时,分析了补货时点优化的效果与供需双方补货次数、需求时变性的关系.     

基于Supply-Hub运作模式的供应商协同补货策略研究

Supply-Hub作为整合管理不同供应商零件库存的供应链节点,同时也承担了供应物流协同运作管理平台的功能.本文考虑加工-装配系统中存在的因一种零件缺货而造成其它配套使用的零件滞存的问题.研究了一种基于Supply-Hub运作模式,在供应商之间可以共享补货及库存信息的条件下,供应商协同补货策略,并与供应商分散补货模式下的基本补货模型进行比较分析.通过算例验证了该补货策略能有效降低供应链系统成本以及供应商成本.     

基于混合差分进化算法的联合补货-配送优化模型

本文综合考虑联合补货与配送决策,研究了随机需求、允许缺货环境下多企业多产品联合补货与配送集成优化模型,设计了混合差分进化算法(Hybrid Differential Evolution, HDE)对该模型进行求解,同时通过算例与遗传算法、标准的DE算法进行了比较,证实HDE算法高效且稳定;另外,设计了一个先补货再配送的两阶段优化模型,对比优化结果发现采用供应链协同时补货成本较高,配送成本较低,且总成本较低。最后,对相关参数进行了敏感性分析,发现需求率和库存维持成本的变动对总成本的影响远远大过次要订货成本对总成本的影响。     

时变需求环境下供应链缺货时点与补货次数优化研究

本文基于博弈模型,研究在时变需求和无替代供应源的环境下供需双方缺货时点和补货次数的纳什均衡问题,并通过算例,具体分析了供需之间的关系,主要结论有:配送商的补货次数越大,零售商库存成本越小;补货次数优化后零售商与配送商的库存成本明显下降。     

部分短缺量拖后下基于顾客敏感度的补货策略适用范围研究

顾客对缺货数量和等待时间的敏感度影响着部分短缺量拖后率。基于此,根据顾客对缺货数量和等待时间的敏感度以及成本结构,对部分短缺量拖后下不同补货策略的适用范围进行了研究,得出以下结论:(s,S)连续性检查策略适用于单位缺货和丢单成本较高的库存系统;(t,S)周期性检查策略和(t,s,S)混合策略适用于单位缺货和丢单成本较低的库存系统;在单位缺货和丢单成本较低的库存系统中,当顾客对缺货数量较敏感时,(t,s,S)混合策略的运作成本更低,否则(t,S)周期性检查策略更适用,而顾客对等待时间的敏感度对补货策略适用范围的影响不明显。     

缺货损失高于补货成本的易逝品供应链协调

本文研究了缺货损失高于补货成本易逝品的供应链契约.在供应链中,制造商具有较长提前期的低成本生产和快速供货的高成本生产两种模式,快速生产模式满足零售商紧急补充订货.由于缺货损失高于补货成本.当订货不能满足需求时制造商快速供货生产模式满足缺货的成本最小化订货策略比允许缺货的订货策略使供应链整体业绩更优.研究了制造商与零售商之间订货、补充订货与退货契约,发现存在合理的契约能协调零售商和制造商行为实现供应链整体成本最优.     

库存成本变化的VMI供应链协调

提出了库存成本变化的经济订货批量(EOQ)模型，基于该模型研究了库存成本变化时供应商管理库存(VMI)系统的最优协议问题。在该系统中，订货商和供应商达成缺货成本共担协议：当缺货发生时，供应商需要向订货商支付缺货补偿。订货商和供应商分散决策，订货商通过设计协议来减少其成本，而供应商通过制定补货决策来缩小自身成本。通过与传统系统和整合系统的比较，得出了库存成本变化时VMI系统的最优补货决策和缺货成本共担协议。采用数值算例验证了分析结果。结果表明，当且仅当供应商预期成本等于整合系统的最小总成本与固定缺货罚金之和时，VMI系统与整合系统具有相同的补货决策和系统绩效，即能够实现供应链协调。     

无人零售业态下自动售卖机联合补货策略研究

研究无人零售业态下自动售卖机的多产品联合补货问题，建立由补货成本、库存持有成本、缺货成本构成的平均补货成本模型，分析容量约束与固定补货阈值下的最优补货策略。结果表明，企业会倾向于在剩余较少产品时进行补货，剩余的产品往往是投影面积最小使得相同面积可容纳最多数量的产品；比较最优补货时间与平均补货成本发现，延长补货时间可以降低平均补货成本，在补货阈值越大、固定补货成本越低或售卖机容量越小时，最优补货时间会降低，反之，平均补货成本会增加。此外，分析不同成本变动对平均成本的影响发现，单位成本变动均会引起平均补货成本的增加，且在单位库存持有成本变动时，最优补货策略会发生转移，向单位库存持有成本降低至一定程度的产品或向投影面积最低即相同面积可容纳数量最小的产品转移。     

允许缺货且具有随机缺陷率的EOQ模型研究

生产系统不完善、自然灾害、运输等因素对传统EOQ模型中产品质量100%合格的假设提出了巨大的挑战.本文考虑了含有缺陷率且允许缺货的库存模型,其中产品检验过程与补货过程同步进行,时间范围是无限的,每个订货周期可以看成是一个更新过程.通过建立具有随机缺陷率的模型,运用更新酬劳过程方法得到期望利润表达式,确定最优订购策略,并且运用具体算例进行了验证,最后通过实验仿真探讨了不同均值和方差下缺陷率对最优订购策略的影响,同时还研究了检验速率和单位持有成本对最优订购策略和期望总利润的影响.     

A hybrid inventory management system responding to regular demand and surge demand

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.     

An integrated vendor-buyer cooperative inventory model for items with imperfect quality

This article develops a model to determine an optimal integrated vendor-buyer inventory policy for flawed items in a just-in-time (JIT) manufacturing environment. The aim is to minimize the total joint annual costs incurred by the vendor and the buyer. The proposed model extends the integrated vendor-buyer inventory model by accounting for imperfect quality items. The expected annual integrated total cost function is derived and an analytic solution procedure is proposed to determine the optimal policy. Finally, numerical examples are also given to illustrate the solution procedure presented in this article.     

基于反向物流的商品定价和退货政策研究

综述了基于反向物流的商品定价和退货政策的最新研究成果。在此基础上,通过建立模型,对基于反向物流的商品定价策略和退货政策进行了进一步的研究,并求出了商品的最优价格和最优退货价格。基于模型,对管理提出了一些建议。最后指出了将来可能的研究方向。     

A reinforcement-learning approach for admission control in distributed network service systems

In the distributed network service systems such as streaming-media systems and resource-sharing systems with multiple service nodes, admission control (AC) technology is an essential way to enhance performance. Model-based optimization approaches are good ways to be applied to analyze and solve the optimal AC policy. However, due to “the curse of dimensionality”, computing such policy for practical systems is a rather difficult task. In this paper, we consider a general model of the distributed network service systems, and address the problem of designing an optimal AC policy. An analytical model is presented for the system with fixed parameters based on semi-Markov decision process (SMDP). We design an event-driven AC policy, and the stationary randomized policy is taken as the policy structure. To solve the SMDP, both the state aggregation approach and the reinforcement-learning (RL) method with online policy optimization algorithm are applied. Then, we extend the problem by considering the system with time-varying parameters, where the arrival rates of requests at each service node may change over time. In view of this situation, an AC policy switching mechanism is presented. This mechanism allows the system to decide whether to adjust its AC policy according to the policy switching rule. And in order to maximize the gain of system, that is, to obtain the optimal AC policy switching rule, another RL-based algorithm is applied. To assess the effectiveness of SMDP-based AC policy and policy switching mechanism for the system, numerical experiments are presented. We compare the performance of optimal policies obtained by the solutions of proposed methods with other classical AC policies. The simulation results illustrate that higher performance and computational efficiency could be achieved by using the SMDP model and RL-based algorithms proposed in this paper.     

具有多元马氏需求的多产品多阶段库存优化模型

本文研究一类新的多产品库存控制策略,即具有多元马氏需求特征的多产品多阶段的订货点订货量(Q, R, SS)策略,该策略考虑市场需求在不同产品之间具有多元马氏转移特征,并考虑缺货因素设置安全库存。论文首先建立了多产品多阶段的多元马氏需求预测模型,并通过该模型确定了各种产品需求之间的关系。同时,在该模型的理论基础上,提出了多产品多阶段的总期望成本模型及其最优(Q, R, SS)策略,进而结合算例给出模型的最优策略的数值解。     

有限时域与采购价格上升情形下的最优订货策略

研究了有限时域下采购商面对价格上升时的订货策略问题.在分析问题的基础上提出一种新的最优采购策略,并分析了价格上升幅度对订货量的影响,以经典EOQ模型的总成本为基准,比较了本文提出的策略与文献已有策略在成本节约上的差异.本文对库存总成本的计算方法更加精确;分析表明在有限时域背景下采购商的临时订货量决定于价格上涨的幅度、在库库存以及时段长度.     

基于收益管理的海运集装箱舱位分配与路径选择优化模型

文章应用收益管理的方法对不确定环境下海运集装箱的舱位分配问题进行了定量研究.首先针对海运收益管理的应用特征,建立了考虑空箱调运和路径选择的集装箱多航段能力分配模型,然后考虑需求的不确定性,应用稳健优化方法对此模型进行求解.最后,通过数值仿真得到了优化的舱位分配方案,比较发现稳健优化模型取得了较确定性规划模型更好的收益.显示了模型和方法对于集装箱海运企业的收益管理问题具有应用价值.     

Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell

This paper considers a joint preventive maintenance (PM) and production/inventory control policy of an unreliable single machine, mono-product manufacturing cell with stochastic non-negligible corrective and preventive delays. The production/inventory control policy, which is based on the hedging point policy (HPP), consists in building and maintaining a safety stock of finished products in order to respond to demand and to avoid shortages during maintenance actions. Without considering the impact of preventive and corrective actions on the overall performance of the production system, most authors working in the reliability and maintainability domains confirm that the age-based preventive maintenance policy (ARP) outperforms the classical block-replacement policy (BRP). In order to reduce wastage incurred by the classical BRP, we consider a modified block replacement policy (MBRP), which consists in canceling a preventive maintenance action if the time elapsed since the last maintenance action exceeds a specified time threshold. The main objective of this paper is to determine the joint optimal policy that minimizes the overall cost, which is composed of corrective and preventive maintenance costs as well as inventory holding and backlog costs. A simulation model mimicking the dynamic and stochastic behavior of the manufacturing cell, based on more realistic considerations of the real behavior of industrial manufacturing cells, is proposed. Based on simulation results, the joint optimal MBRP/HPP parameters are obtained through a numerical approach that combines design of experiment, analysis of variance and response surface methodologies. The joint optimal MBRP/HPP policy is compared to classical joint ARP/HPP and BRP/HPP optimal policies, and the results show that the proposed MBRP/HPP outperforms the latter. Sensitivity analyses are also carried out in order to confirm the superiority of the proposed MBRP/HPP, and it is observed that for practitioners, the proposed joint MBRP/HPP offers not only cost savings, but is also easy to manage, as compared to the ARP/HPP policy.     

EOQ-based inventory management in single-machine multi-item systems

The present paper proposes an approach for including the finite capacity constraint in the EOQ model (and, in more general terms, in inventory systems) to study the context of single-machine multi-item systems. In particular, the proposed approach regulates the processing of different items by a shared resource according to a control model based on an ordering policy that combines the Economic Order Quantity with a policy based on minimum and maximum inventory levels (min–max policy). To achieve such a challenging result, the present work exploits the analogy between “switched arrival systems” (a particular class of hybrid systems) and min-max inventory systems. The development and parameterization of the abovementioned control model, therefore, refers to switched arrival systems control theory and mixed-integer linear programming. The present work also contributes to the integration of static tools (i.e., the EOQ model) and control tools, approaching these areas. The paper concludes with a real case application that illustrates the proposed approach and allows for a future research path to be drawn.     

带学习效应的双渠道供应链库存策略研究

针对具有学习行为的双渠道供应链问题,本文研究了两种分销渠道并存下的最优库存策略。有限计划期内,分销商通过传统销售和在线销售来满足下游顾客的需求。两种分销渠道下的销售单价为时变不减线性函数,当系统中各周期的生产订购固定成本以一定的概率具有学习效应行为时,分别建立了非变质产品生产存贮问题的混合整数约束优化模型以及易变质产品存贮问题的无约束混合整数优化模型,所建立模型的目标为极大化分销商总利润函数。对于这两类模型,通过分析其最优解的性质,利用将生产订购次数松弛为连续变量的技巧证明了最优解存在的唯一性。给出了最优策略的求解方法并比较了两类模型最优利润函数值的大小。最后通过数值算例对上述模型进行了验证,数值结果表明当供应链系统中存在学习效应行为时,该系统能够获得更多的利润。