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．

     

需求依赖库存且短缺量部分拖后的促销商品库存模型

促销商品是商场吸引顾客前往购买消费的一种重要手段,它可以有效带动其他商品的销售从而提高商场销售收入。考虑促销商品在缺货期间价格和时间对顾客等待行为的影响,构造了一个与销售价和等待时间相关的短缺量拖后率,建立了多次订货下两阶段存货影响需求和顾客等待的促销商品库存模型,并利用仿真方法分析价格和时间敏感因子、存货影响需求临界点、销售价格对销售商订货策略和系统总利润的影响。结果表明：价格和时间敏感因子对各周期服务水平影响显著,存货影响需求临界点对订货次数影响较大;当销售价在一定范围时,销售商只需调整各周期服务水平,而当销售价过高或过低时,销售商则需同时调整各周期服务水平和订货次数     

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.     

需求依赖库存且有时变短缺拖后率的非立即变质物品库存模型

研究了时变短缺部分拖后条件下非立即变质性物品的库存补给模型,其中物品的变质率随时间变化而变化。当库存水平为正值时,市场需求受销售价格影响;当库存为负值时,不能满足的需求被部分拖后,拖后率与在缺货期间已经发生的缺货量有关。通过考虑短缺拖后率和变质率同时随时间变化对库存补给策略的影响,建立具有短缺量部分拖后的非立即变质性物品的库存模型,并且给出模型最优解存在的必要条件,得到一类更加符合实际情形的库存模型。最后,用数值算例说明模型的实际应用。     

需求随机依赖库存环境下的订货仿真优化模型

需求的随机性和依赖库存性是库存问题的特点之一,在需求以泊松分布的形式随机依赖库存的条件下讨论了（Q,T）型库存控制问题。为了评估库存控制策略的平均盈利水平,建立了该库存问题的离散事件系统仿真模型,设计了一种基于仿真的种群重叠、遗传操作非重叠的进化算法,用以优化库存控制策略,类似设计了基于仿真的模拟退火和粒子群优化算法进行比较。通过实例分析了不同参数的变化对模型最优解的影响,灵敏度分析表明需求依赖库存效应越明显时,利润水平越高,最优订货策略越倾向于高库存、短周期和现货销售。仿真实例说明了基于仿真的优化算法的可行性、有效性。     

随机需求下的供应链库存控制策略研究

考虑了由多个供应商、一个配送中心组成的二级供应链系统在市场需求为随机情况下的多品种库存问题。通过确定各变量之间的关系,以配送中心损失期望值最小为目标函数,建立了一个混合整数非线性规划模型;利用求解多元函数条件极值的办法来求解该问题模型;最后给出了一个算例进一步诠释了该解法,从而丰富了在面对市场为随即需求下的多品种库存控制策略的研究工作。     

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.     

需求随机的变质性产品生产计划模型

研究了能力约束的有限计划展望期生产计划问题,各周期的需求随机,库存产品存在变质且变质率为常数。建立了问题的期望值模型,目标函数为极小化生产准备成本、生产成本、库存成本的期望值。提出了随机模拟、遗传算法和启发式算法相结合的求解算法。用数值实例对模型和算法进行了验证,优化结果表明模型和算法是有效的。     

一种多周期随机需求生产/库存控制方法

为了合理地对库存进行管理,使得产品的存贮、生产和缺货等费用的总和最小,建立了一种多周期随机需求生产／库存模型．该模型采用（s,Q）策略对生产和库存进行控制,即当成品库存降至S时准备生产,生产量为Q．通过对模型费用函数特性的分析,设计了一种最优生产控制算法,根据该算法可以得出系统的最优生产准备点和最优生产量．理论分析和计算结果表明,该方法可以有效地减小系统生产和库存的平均费用．     

随机时变需求下有阶段和总量约束的多源采购优化

针对有阶段采购量区间约束及最小总量要求的多供应商多阶段订单分配问题,以采购方采购、库存、缺货成本总和与期末库存残值之差的期望值最小为目标,建立随机非线性规划模型.考虑采购量约束及多供应商情形,扩展报童模型得出单阶段最优采购策略.以此为基础建立多阶段启发式算法,通过仿真分析各参数对最优采购策略及其总成本的影响.将最小总量承诺契约扩展到时变需求和多供应商情形,可为采购方降低成本.     

Supply chain coordination with two production modes and random demand depending on advertising expenditure and selling price

This article discusses production and order as well as advertising coordination issues in a single-manufacturer single-buyer supply chain, where the manufacturer sells a newsvendor-type product through the buyer who faces a random demand depending on advertising expenditure and selling price. The buyer has two ordering opportunities: the one happens before the beginning of the season, and the other takes place at the end of the season. The ordered items are produced by the manufacturer in two production modes for different requirements. The first production mode is relatively cheap but requires a long lead-time, whereas the second is expensive but offers quick response. Under such a setting, the centralised and decentralised decision models are developed, respectively, and the closed form solution to each model is provided as well. Moreover, we point out that the traditional revenue-sharing contract fails to coordinate the supply chain. We thus propose an improved revenue-sharing contract that requests the manufacturer not only shares the buyer's revenue but also bears a portion of the buyer's operating costs. Such a contract can achieve perfect coordination of the supply chain and arbitrarily allocate its profit between two parties.     

Inventory model for seasonal demand with option to change the market

In real life, when bulk purchase becomes convenient or even mandatory, it is a common practice for distributors to explore an alternative market in order to maximize the revenue earned. In this paper, we consider an inventory model for a product having seasonal demand with two potential markets, say, primary and alternate. The distributor has a single opportunity of procurement prior to multiple demand seasons in the primary and the alternate market. Both the markets have similar demand patterns, with time lag between their demand seasons. The demand is a price and time dependent function with increasing, constant and declining phases within each demand season. The scale parameter of demand rate depends upon the market. In each market, successive seasons are separated by random time. In one replenishment cycle, the distributor has a single option to exit the primary market by transferring the inventory, with or without change in selling price. This option can be exercised at the end of any complete season at the primary market. Our investigations indicate that it will be beneficial for the distributor to shift to the alternate market even at a slightly lower selling price if demand rate in the alternate market is higher. Optimal number of seasons at the primary market before change of price or market is obtained. Optimal policy is obtained for jointly determining the order quantity and price. Concavity of the profit function is discussed. Solution procedure, numerical examples and sensitivity analysis are presented.     

合作连锁营销下随机需求的分销系统双层补货优化控制模型

研究在每一补货间隔内需求为服从有限区间上渐变对称分布的随机变量的各零售商集体与一个地区分销中心组成的地区分销系统.分销系统中各零售商可独立决定所经营卖场的补到水平,补货周期是固定值;分销中心给各零售商送货,送货循环周期固定,各零售商补货周期等于分销中心送货循环周期.假定零售商顾客需求是均匀发生的,给出了零售商补到水平优化控制策略和分销中心进货控制策略.最后,通过一个算例验证了该模型的有效性.     

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.     

Finite horizon EOQ model for non-instantaneous deteriorating items with price and advertisement dependent demand and partial backlogging under inflation

This paper deals with an economic order quantity (EOQ) model for non-instantaneous deteriorating items with price and advertisement dependent demand pattern under the effect of inflation and time value of money over a finite planning horizon. In this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This paper aids the retailer in minimising the total inventory cost by finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented and the implications are discussed in detail.     

Inventory policy of a deteriorating item with variable demand under trade credit period

In this paper, an inventory model of a deteriorating item with stock and selling price dependent demand under two-level credit period has been developed. Here, the retailer enjoys a price discount if he pays normal purchase cost on or before the first level of credit period, or an interest is charged for the delay of payments. In return, retailer also offers a fixed credit period to his customers to boost the demand. In this regard, the authors develop an EOQ model incorporating the effect of inflation and time value of money over all the costs. Keeping the business of seasonal products in mind, it is assumed that planning horizon of business is random and follows a normal distribution with a known mean and standard deviation. The model is formulated as retailer’s profit maximization problem for both crisp and fuzzy inventory costs and solved using a modified Genetic Algorithm (MGA). This algorithm is developed following fuzzy age based selection process for crossover and gradually reducing mutation parameter. For different values of MGA parameters, optimum results are obtained. Numerical experiments are performed to illustrate the model.     

A note on the inventory model for deteriorating items with trapezoidal type demand rate

In this paper, we study the inventory model for deteriorating items with trapezoidal type demand rate, that is, the demand rate is a piecewise linearly function. We proposed an inventory replenishment policy for this type of inventory model. The numerical solution of the model is obtained and also examined.     

“电脑”型产品需求预测的Gompertz模型与随机模拟

“电脑”型产品包括手机、电视机、电脑等无形性变质产品,这种产品需求波动性大,随机性强、历史数据失效或根本不存在历史数据,其需求量的预测往往比常规品更为困难。介绍了“电脑”型产品需求预测的Gompertz模型,并应用这个模型对2010年长沙市电脑需求情况进行了预测,通过计算机随机模拟,对2010年长沙市手机产品的需求量也进行了预测,取得了较好的效果。为进一步研究“电脑”型产品库存控制问题提供了较好的基础。