模糊环境下可控提前期供应链库存优化的Stackelberg模型研究

为了有效地缩短提前期与降低库存成本,研究了模糊环境下可控提前期的供应链库存优化问题.利用三角形模糊数描述需求的不确定性,建立了一类模糊需求条件下可控提前期供应链库存优化的Stackelberg模型.利用三角形模糊数描述成本系数的不确定性,建立了模糊成本系数条件下可控提前期供应链库存优化的Stackelberg模型,并提出利用均值面积度量法来解模糊化.通过数值分析来验证两类模型的优化效果.     

需求受库存影响下具有固定保质期物品的最优订货策略

带有固定保质期物品的订货是供应链终端销售系统的一个重要决策问题,假设需求依赖库存展示水平并考虑"后进先出"的销售策略而建立了相应的库存决策模型,其中物品在固定保质期内仍具有常数的变质速率.然后以系统平均利润最大化为目标讨论了模型最优解的存在性及唯一性,并提供了寻求模型整体最优解的简单方法.最后给出应用实例,并分析了模型参数变化对最优订货策略的影响.     

需求不确定情况下的多周期生产批量决策

针对在市场需求不确定的情况下的中小制造型企业的生产批量决策优化问题进行研究,根据多周期生产情况下需求的不确定性,综合考虑缺货成本、库存成本和期初库存等因素,以多生产周期的总利润最大化为目标,建立生产批量决策模型,通过优化分析,得出其利润最大化下的最优生产批量,并通过敏感性分析讨论最优批量与多周期生产条件下的不确定需求等影响因素之间的关系.     

顾客搜索强度影响下短生命周期产品订货决策

根据短生命周期产品的特点,考虑与需求相关的顾客搜索强度,在假设溢出需求为顾客搜索强度函数的情况下,建立了考虑顾客搜索强度因素的斜坡型需求模型,分两种情形对模型最优解进行了存在性证明和求解.然后通过数值算例分析了主要参数变化对缺货时间、订货量、库存成本的影响,发现订货量与顾客搜索强度同方向变动,缺货时间与需求变化临界点出现先后的不同,缺货成本、持有成本和变质成本对库存总成本的影响不同.     

智能电表最优更换及备件库存联合决策

智能电表是智能电网运行的关键部件,提高其可靠性和可用度对保证电力的持续不间断供应和准确电能测量至关重要。充足的智能电表库存是其换装与维修的基本保障。本文基于智能电表的故障特性和换装需求分析,建立了智能电表的最优更换与备件库存联合决策模型,并给出了优化方法,以求得可以使系统长期平均运营成本最小的最优更换与备件库存策略。     

弹性需求下可控提前期供应链库存优化的信用期机制

研究了弹性需求下可控提前期供应链库存优化的信用期机制,在一个固定订货间隔期模型中,假设需求与价格相依,且提前期可以通过额外的赶工成本进行压缩的情况下,分别考虑了买卖双方合作和不合作情形下的最优定价、订货和信用期决策.最后通过数值分析进行验证,并建立Nash协商模型进行利益分配.     

提前期可控的模糊需求周期盘点补充订货模型研究

为解决具有模糊需求的可控提前期库存管理问题,建立了提前期和盘点周期作为决策变量的周期性盘点补充订货模型,采用符号距离方法对模型进行反模糊化求解,并设计了一确定其最优存储策略的算法。结合算例分析了需求的模糊性对最优盘点周期和最小成本的影响。     

ARMA(1,1)需求条件下供应链需求提前承诺的影响效果分析

为了分析供应链需求提前承诺的影响效果,考虑供应链所面临的顾客需求满足ARMA（1,1）过程。首先从理论上建立正常顾客需求与顾客需求提前承诺时零售商订单量波动程度和平均库存的定量描述模型,通过两种情形下的比较分析,得出在顾客需求自回归系数大于零时,顾客需求提前承诺将减小牛鞭效应和平均库存水平;同时得出在顾客需求提前承诺时,如果顾客需求自回归系数大于零,顾客提前承诺的需求比例越高,则牛鞭效应和平均库存水平越低;顾客需求提前承诺的时间跨度越长,则牛鞭效应和平均库存水平也越低。反之亦然。其次运用仿真方法分析了顾客需求提前承诺对零售商平均库存成本的影响,得出在顾客需求自回归系数大于零时,顾客需求提前承诺将有效降低零售商的平均库存成本。     

库存展示量影响需求的促销易腐品最优订货策略

零售商经常会选择多种商品进行促销以提高收益,促销商品与人民群众的日常生活密切相关。本文建立库存影响需求的促销易腐品的订货决策模型,允许缺货发生,且短缺拖后率与已经发生的缺货量和等待时间相关。证明了最优解的存在性和唯一性,提出了求解最优订购策略的搜索算法。通过仿真实验验证模型和算法,得到主要参数的灵敏度分析结果。     

变换核估计在未知需求分布函数条件下多阶段库存控制策略中的应用研究

传统的多阶段库存控制主要致力于库存持有以及过多库存的经济性研究.随机库存模型经常假定需求分布已知,这样可以产生容易解决的方案.但随着销售信息的不断更新,需求分布函数的参数常常未知.这样传统的多阶段库存模型很难产生最优的库存控制策略.当前文献对未知需求分布函数条件下的多阶段库存管理问题研究得不多,当需求分布函数随时间变化,是个多阶段随机规划问题,通常情况难以直接进行求解.针对一般非平稳需求,还缺少有效的库存管理方法.本文致力于变换核估计和优化理论相结合的方法研究未知需求分布函数条件下多阶段库存控制策略,提供一条多阶段库存控制的新思路.可以很好地确定各阶段的最优订货点、最高库存、最低库存等来达到整个系统的最优,从而节省更多的成本,达到营运资本的永久性减少、更高的销售量和客户满意度,从而增加企业的竞争力.     

A multi-item mixture inventory model involving random lead time and demand with budget constraint and surprise function

This study deals with a multi-item mixture inventory model in which both demand and lead time are random. A budget constraint is also added to this model. The optimization problem with budget constraint is then transformed into a multi-objective optimization problem with the help of fuzzy chance-constrained programming technique and surprise function. In our studies, we relax the assumption about the demand, lead time and demand during lead time that follows a known distribution and then apply the minimax distribution free procedure to solve the problem. We develop an algorithm procedure to find the optimal order quantity and optimal value of the safety factor. Finally, the model is illustrated by a numerical example.     

Inventory model involving controllable backorder rate and variable lead time demand with the mixtures of distribution

In the model of Ouyang and Chuang [Comput. Ind. Eng. 40 (2001) 339], they assume that the backorder rate is dependent on the length of lead time through the amount of shortages and let the backorder rate is a control variable. But, since they only assumed a single distribution for the lead time demand, when the demand of the different customers are not identical in the lead time, then we cannot use a single distribution (such as [Comput. Ind. Eng. 40 (2001) 339]) to describe the demand of the lead time. Hence, in our studies, we first assume that the lead time demand follows a mixtures of normal distribution, and then we relax the assumption about the form of the mixtures of distribution functions of the lead time demand and apply the minimax distribution free procedure to solve the problem. We develop an algorithm procedure, respectively, to find the optimal order quantity and the optimal lead time. Furthermore, two numerical examples are also given to illustrate the results.     

An integrated inventory model with controllable lead time and distribution‐free demand

The impact of lead time reduction on an integrated periodic review inventory system comprising a single vendor and multiple buyers with a step crashing cost function and service‐level constraints is studied. The probability distribution of demand during the protection period for each buyer is unknown, but the mean and the variance are given. Each production lot of the vendor can be delivered in a number of shipments to all buyers. A minimax distribution‐free procedure with Lagrange multipliers is applied to determining the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost is minimized. Numerical experiments along with sensitivity analysis were performed to illustrate the effects of parameters on the decision and the total system cost. Copyright © 2009 John Wiley & Sons, Ltd.     

分布自由时基于可控提前期的契约适应性研究

研究表明回购契约与收益共享契约具有等价性,然而二者却适用于不同的供应链。本文从提前期可控的视角并将供应链管理引入需求分布自由的市场环境,研究二者的适应性。首先构建一体化供应链系统的决策模型,基于模型推导其最优生产量和最优生产时点的存在性条件;然后分别以回购契约和收益共享契约作为激励机制,研究契约对单一供应商-零售商构成的二级分散供应链系统的适应性。结果表明,回购契约和收益共享契约均能协调供应链,但二者具有不同的适应性:当单位时间内边际生产成本增幅较大时,供应商偏好选择回购契约;提前压缩期越长,零售商越偏好选择收益共享契约。最后通过数值分析验证文章模型的有效性。     

Reducing lost-sales rate on the stochastic inventory model with defective goods for the mixtures of distributions

In this paper, we assume that the demands of different customers are not identical in the lead time. Thus, we investigate a continuous review inventory model involving controllable lead time and a random number of defective goods in buyer’s arriving order lot with partial lost sales for the mixtures of distributions of the lead time demand to accommodate more practical features of the real inventory systems. Moreover, we analyze the effects of increasing investment to reduce the lost sales rate when the order quantity, reorder point, lost sales rate and lead time are treated as decision variables. In our studies, we first assume that the lead time demand follows the mixture of normal distributions, and then relax the assumption about the form of the mixture of distribution functions of the lead time demand and apply the minimax distribution free procedure to solve the problem. By analyzing the total expected cost function, we develop an algorithm to obtain the optimal ordering policy and the optimal investment strategy for each case. Finally, we provide numerical examples to illustrate the results.     

Improved solution for inventory model with defective goods

This paper is a consequence for a paper of Lin et al. [S.W. Lin, Y.W. Wou, P. Julian, Note on minimax distribution free procedure for integrated inventory model with defective goods and stochastic lead time demand, Appl. Math. Model. 35 (2011) 2087–2093]. We simplified their complicated solution procedure and then presented a revision to patch their negligence for the boundary minimums. Numerical examples are provided to demonstrate our findings.     

Order release planning by iterative simulation and linear programming: Theoretical foundation and analysis of its shortcomings

Planning future order releases for complex manufacturing systems with substantial lead times must consider limited capacities and the resulting production smoothing problem as well as the highly nonlinear relationship between capacity utilization, work-in-process and flow times. An important solution approach that has been proposed for this problem is to iterate between an order release model with fixed lead times and a lead time estimation (usually simulation) model that estimates the flow times for given order releases, providing the lead times for the next iteration. However, the convergence of this iterative procedure is highly unpredictable, limiting its practical use.The iterative mechanism is analyzed analytically for simplified formulations of the order release and lead time estimation model. We show that an order release procedure of this type that iterates on the lead times is a dual (price) coordination mechanism whose design does not meet the theoretical requirements, and there is no straightforward way to overcome this. The analysis also provides insights into the results of several numerical studies from the literature and suggests a possible research direction to improve the method.Order release mechanisms of this type are a special case of a broader class of production planning methods that iterate between the production planning and the production scheduling level in order to provide realistic values for lead times and planned capacities. Providing theoretical underpinning for this type of production planning methods is an important research objective, and the paper pursues this direction for the special case of order release.     

Distribution Free Procedures for Some Inventory Models

Stochastic inventory models, such as continuous review models and periodic review models, require information on the lead time demand. However, information about the form of the probability distribution of the lead time demand is often limited in practice. We relax the assumption that the cumulative distribution function, say F, of the lead time demand is completely known and merely assume that the first two moments of F are known and finte. The minmax distribution free approach for the inventory model consists of finding the most unfavourable distribution for each decision variable and then minimizing over the decision variable. We solve both the continuous review model and the periodic review model with a mixture of backorders and lost sales using the minmax distribution free approach.     

Integrating effective flexibility measures into a strategic supply chain planning model

This paper develops models for capacity, product mix, distribution and input supply flexibility and integrates them in a strategic level, mixed integer supply chain (SC) planning model as a way of addressing demand and supply uncertainty, as well as improving market responsiveness. Capacity flexibility is modeled via the SC’s production capacity planning to address budgeted demand and ensure the fulfillment of prospective demand increases when considering various market scenarios. This model selects an optimal number of products from fast moving and extended product range options—based on the product mix flexibility. The model confirms a quick response to a changing marketplace by considering elements like transportation and supply lead time along with the probabilities of stock out options when addressing input supply and distribution flexibility. This paper proposes a solution procedure to solve the model for real world problems, and investigates the sensitivity of the model outputs with respect to changes in flexibility measures.     

Are more suppliers better?: generalising the Guo and Ganeshan procedure

In multiple supplier inventory models, where several suppliers are used to replenish the stock of one item, computation of mean and variance of supplier lead times requires the knowledge of the moments of order statistics from the parent lead time distribution. This article presents a general procedure of finding the moments of supplier lead times in multiple supplier inventory models. The procedure is based on using the Generalised Lambda Distribution (GLD) to approximate the lead time distribution. Numerical examples are provided to validate our procedure. The proposed procedure has the advantage that the computations involved are very simple and can be used for any continuous unimodal lead time distribution.