带有两次订购机会且两阶段需求相关的Newsboy模型

首先建立需求形式为一般随机变量情形下零售商的两次订购决策模型,并从理论上证明了在两个阶段需求相互独立情形下,零售商期望利润函数的下凹性及最优订购策略的存在唯一性,从而弥补了已有模型在寻求最优订购策略时采用数值方法所存在的缺憾;然后,建立两阶段需求相关情形下带有两次订购的Newsboy模型,给出了模型的分析解.数值实例验证了模型的求解过程,并得到了相关管理启示.

     

两阶段需求相关的动态易逝品最优订货策略

以动态市场环境下的易逝品为研究对象,针对两阶段需求相关、每次订货时带有固定的订购费用以及未满足需求部分延期供给等实际现象,建立了动态易逝品销售商两阶段订货决策模型.对模型的最优解进行了理论分析,并提出了寻求两阶段订货策略的简单方法.以朗科优盘经销商的采购实例来说明该模型的应用价值.最后,通过探讨订货决策与需求波动、两阶段需求相关系数以及延期供给率等因素的关系,得出了一些重要的管理启示.     

两种需求模式下报童模型的最优定价-订购联合决策

在加法和乘法两种需求模式下,研究了带有缺货惩罚的单周期报童模型的最优定价-订购联合决策问题,证明了最优决策的存在性及唯一性的充分条件,并具体给出了最优决策的解析表达式。通过数值算例,验证了结论的有效性,给出了价格敏感因子对最优决策和期望收益的影响。研究结果在理论上更具有一般性,而且为研究多零售商的价格竞争决策问题和供应链契约协调等问题提供了理论依据。     

一种激励相容的用户需求订购模型

用户基准负荷(CBL)是实施激励性补偿驱动的需求响应(DR)项目的关键因素之一.由于信息不对称,传统的基于历史数据的用户基准负荷估计会导致操纵问题,从而影响需求响应项目的经济效率.基于机制设计理论,引入类型参数来描述用户的用电需求意愿;提出了信息不对称环境下,供电公司考虑用户参与约束和激励相容约束的需求订购模型及其求解方法,该模型能激励用户披露真实的基准负荷信息.最后通过算例仿真验证了所提出模型的有效性和合理性.     

一种需求率随时间变化且允许缺货的库存模型

针对库存管理和控制中存在的实际问题,在最大程度降低库存运营成本的前提下,综合考虑了货物损坏率以及缺货率引起的损失等多种影响,提出了一个需求率为一般连续函数的库存模型,并进一步建立了该模型的两阶段优化方法.该方法通过简单的求解过程,就能够找到最优订货策略,从而有效的降低了库存成本.最后运用一个简单的数据实验,证明了该模型和方法的有效性和准确性.该库存成本函数模型及其求解方法也可以适用于需求率是非单调的随时间变化函数的模型.     

随机需求下供应链企业订购多Agent协商模型

针对随机需求下供应链产销订购冲突问题,考虑一个制造商和两个零售商组成的两级供应链,构建主从博弈下的多Agent协商模型。制造商作为博弈主方制定批发价,零售商作为从方选择最优订货量和零售价,制造商Agent和零售商Agent自动协商,运用模拟退火算法寻求模型的最优解。通过算例发现合理的让步策略和收益共享契约能够提高供应链系统利润,实现产销双方的互利共赢。验证模拟退火算法求解该模型比遗传算法能够得到更优解。     

库存水平影响需求下变质品订购、定价和保鲜技术投资的联合决策

研究变质品的订购、定价和保鲜技术投资联合决策问题.假设产品需求同时受价格和库存水平的影响,系统不允许缺货并放松期末库存水平为零的约束,零售商拥有有限的货架空间或存储空间,同时考虑零售商可以通过投资保鲜技术减低产品的变质率,以平均利润最大化为目标构建库存水平影响需求下变质品的订购、定价和保鲜技术投资联合决策模型.首先证明最优策略的存在性和唯一性,并给出零售商建立期末库存的条件;然后利用最优解的相关性质设计一个求解模型的多阶段迭代算法;最后通过具体算例验证展示模型和算法的可行性和实用性,并完成相关参数的敏感性分析,获得一定的管理启示.     

两级供应链联合成本三角模糊需求随机过程模型

根据影响两级供应链系统库存控制及决策过程的随机与模糊特性,基于联合成本提出两级供应链三角模糊需求随机过程模型。对两级供应链系统进行研究,给出其联合成本优化模型。针对交货时间和需求率的模糊特性,分情况利用三角模糊函数设计缺货数量模糊模型,基于此对两级供应链联合成本优化模型进行改进,建立三角模糊需求随机过程模型,并给出该模型的求解过程。通过模型参数敏感性实验以及算法对比实验,验证了所提模糊随机过程模型的有效性。     

风险规避零售商期末二次订购的供应链决策模型

以风险规避零售商和风险规避供应商组成的两层供应链系统为研究对象, 在条件风险估值的风险度量准则下讨论两生产模式下风险规避零售商的最优订购策略和风险规避供应商的最优生产策略. 通过数值实验得出如下结论: 若零售商的风险规避度越小, 则零售商的第1 次最优订购量越多, 风险利润越大; 供应商的第1 次最优生产量随着供应商的风险规避度减小而增大; 零售商的风险规避度越小, 越不利于供应商的生产投机行为.

     

油田措施配置的随机机会约束规划模型

以油田措施增产最大化为目标,兼顾成本、措施量等目标,建立了油田措施配置的随机机会约束规划模型,并给出了模型的混合智能算法。实例表明,该模型理论基础严格,求解方法科学有效,并具有一定的智能性,为油田措施配置提供了新的决策依据。     

需求依赖广告费用和销售价格的newsboy型产品库存模型

在假定随机需求是关于销售价格和广告费用的一般函数的前提下,提出一个新的ｎｅｗｓｂｏｙ模型,给出了寻求最优广告费用、销售价格及订货量的分析方法,并且还分析了需求的不确定性对最优销售价格和广告策略的影响．最后,通过数值实例验证了模型的求解过程并得到相关管理启示．     

A multi-warehouse inventory model for items with time-varying demand and shortages

This paper develops a deterministic replenishment model with multiple warehouses (one is an owned warehouse and others are rented warehouses) possessing limited storage capacity. In this model, the replenishment rate is infinite. The demand rate is a function of time and increases at a decreasing rate. The stocks of rented warehouses are transported to owned warehouse in continuous release pattern. The model allows shortages in owned warehouse and permits part of the backlogged shortages to turn into lost sales—which is assumed to be a function of the currently backlogged amount. The solution procedure for finding the optimal replenishment policy is shown. As a special case of the model, the corresponding models with completely backlogged shortages and without shortages are also presented. The models are illustrated with the help of numerical examples. Sensitivity analysis of parameters is given in graphical form.Scope and purposeIn practical inventory management, there exist many factors like an attracted price discount for bulk purchase, etc. to make retailers buy goods more than the capacity of their owned warehouse. In this case, retailers will need to rent other warehouses or to rebuild a new warehouse. However, from economical point of views, they usually choose to rent other warehouses. If there are multiple warehouses available, an important problem faced by the retailers is which warehouses to be selected to hold items replenished, when to replenish as well as what size to replenish. For such a problem, the existing two-warehouse models, based on an unrealistic assumption that the rented warehouse has unlimited storage capacity, presented some procedures for determining the optimal replenishment policy. This paper extends the existing two-warehouse models in three directions. Firstly, the traditional two-warehouse models assumed the storage capacity of the rented warehouse unlimited. The present paper relaxes this impractical assumption and considers the situation with multiple rented warehouses having a limited capacity. Secondly, the traditional two-warehouse models considered a constant demand rate or a linearly increasing demand rate. In this model, the demand rate varies over time and increases at a decreasing rate, which implies an increasing market going to saturation. Thirdly, we extend the two-warehouse models to the case with partially backlogged shortages. The purpose of this paper is to build a multi-warehouse replenishment model to help decision-makers solve the problem of which warehouses to be chosen to store items replenished and how to replenish.     

The joint model of the logistic model and linear random effect model — An application to predict orthostatic hypertension for subacute stroke patients

Stroke is a common acute neurologic and disabling disease. Orthostatic hypertension (OH) is one of the catastrophic cardiovascular conditions. If a stroke patient has OH, he/she has higher chance to fall or syncope during the following courses of treatment. This can result in possible bone fracture and the burden of medical cost therefore increases. How to early diagnose OH is clinically important. However, there is no obvious time-saving method for clinical evaluation except to check the postural blood pressure.This paper uses clinical data to identify potential clinical factors that are associated with OH. The data include repeatedly observed blood pressure, and the patient’s basic characteristics and clinical symptoms. A traditional logistic regression is not appropriate for such data. The paper modifies the two-stage model proposed by Tsiatis et al. (1995) and the joint model proposed by Wulfsohn and Tsiatis (1997) to take into account of a sequence of repeated measures to predict OH. The large sample properties of estimators of modified models are derived. Monte Carlo simulations are performed to evaluate the accuracy of these estimators. A case study is presented.     

Integrated inventory control and inspection policies with deterministic demand

In this paper, we develop integrated inventory inspection models with and without replacement of nonconforming items. Inspection policies include no inspection, sampling inspection, and 100% inspection. We consider a buyer who places an order from a supplier. When a lot is received, the buyer uses some type of inspection policy. The fraction nonconforming is assumed to be a random variable following a beta distribution. Both the order quantity and the inspection policy are decision variables. In the inspection policy involving determining sampling plan parameters, constraints on the buyer and manufacturer risks are set in order to obtain a fair plan for both parties. A solution procedure for determining the operating policies for inventory and inspection consisting of order quantity, sample size, and acceptance number is proposed. Numerical examples are presented to conduct a sensitivity analysis for important model parameters and to illustrate important issues about the developed models.     

An economic production lot size model with increasing demand, shortages and partial backlogging

In this paper, an economic production quantity model is developed for a production–inventory system where the demand rate increases with time, the production rate is finite and adjustable in each cycle over an infinite planning horizon and shortages are permitted. The cost of adjusting the production rate depends linearly on the magnitude of the change in the production rate. During the stock‐out period, a known fraction of the unsatisfied demands is backordered while the remaining fraction is lost. The model is formulated taking the demand rate as a general increasing function of time and the optimal production policy is obtained for the special case of a linearly increasing demand rate. The proposed model is also shown to be suitable for a prescribed time horizon. A procedure to find approximately the minimum total cost of the system over a finite time horizon is suggested. A numerical example is taken to illustrate the solution procedure of the developed model.     

A mixed inventory model with variable lead time and random back-order rate

In this paper, we study the determination of the optimal lead time, reorder point and order quantity considering that the back-order probability of a demand made during a stock-out period depends on the interval from the moment in which the order is placed until the next replenishment. Two models are analysed for the specification of the back-order probability: exponential functions and piecewise constant functions. The distribution of the lead time demand is assumed to be Poisson. An algorithm for the determination of the optimal order quantity, reorder point and lead time is given. A numerical example is presented to illustrate the results.     

An accurate and reliable solution procedure for the EOQ model with deteriorating items under supplier credits linked to the ordering quantity

The inventory problem consists of two parts: (1) the modelling and (2) the solution procedure. The modelling can provide insight to solve the inventory problem and the solution procedure involves the implementation of the inventory model. Basically, the modelling and the solution procedure to the inventory problem are equally important. Chang et al.’s inventory model [Chang, C. T., Ouyang, L. Y., & Teng, J. T (2003). An EOQ model with deteriorating items under inflation when supplier credits linked to order quantity. Applied Mathematical Modelling, 27, 983–996] is correct and interesting. However, they ignore the explorations of the functional behaviors of the annual total relevant cost to locate the optimal solutions such that proofs of their solution procedures are not perfect from the viewpoint of logic. The main purposes of this paper are to provide accurate and reliable solution procedures to improve [Chang, C. T., Ouyang, L. Y., & Teng, J. T (2003). An EOQ model with deteriorating items under inflation when supplier credits linked to order quantity. Applied Mathematical Modelling, 27, 983–996].     

An optimization approach for joint pricing and ordering problem in an integrated inventory system with order-size dependent trade credit

Under a business trading environment, it is common for the trade credit to depend on the order size. Therefore, it is important to discuss the single-supplier and single-buyer supply chain problem which includes order-size dependent trade credit. In this study, an integrated inventory model with a price sensitive demand rate, determining jointly economic lot size of the buyer’s ordering and the supplier’s production batch, are developed to maximize the total profit per unit time. An efficient algorithm is provided to obtain the optimal solution, and then numerical examples are presented to illustrate the theoretical results. Finally, the comparison between whether an optimal solution is jointly or independently determined is also provided.     

Maximizing profits in an inventory model with both demand rate and holding cost per unit time dependent on the stock level

We study an EOQ inventory model with demand rate and holding cost rate per unit time, both potentially dependent on the stock level. The ordering cost, the holding cost and the gross profit from the sale of the item are considered. The objective is to maximize the average profit per unit time. We present the analytical formulation of the problem and demonstrate the existence and uniqueness of the optimal cycle time, giving a numerical algorithm to obtain it. Moreover, we provide two fundamental theoretical results: a rule to check when a given cycle time is the optimal policy, and a necessary and sufficient condition for the profitability of the system. Several EOQ models analyzed by other authors are particular cases of the one here studied. We present some numerical examples to illustrate the proposed algorithm and analyze the sensitivity of the optimal solution with respect to changes in various parameters of the system.     

Dynamical analysis of a delayed predator-prey model with impulsive diffusion between two patches

In this work, we propose a delayed predator–prey model with impulsively diffusive prey between two patches. Using the stroboscopic map of the discrete dynamical system, we obtain the globally attractive condition of predator-extinction periodic solution of the system. We also obtain the permanent condition of the system by the theory of impulsive delay differential equation. Our results indicate that the discrete time delay has influence to the dynamical behaviors of the system. Finally, the numerical analysis is inserted to illustrate the results.