存货影响销售率且理论需求为线性时变函数时的EOQ模型

本文建立了理论需求率为线性时变递增函数且无短缺量拖后和短缺量完全拖后时的EOQ模型,并对无短缺量拖后时模型最优解的存在及唯一性进行了讨论,为库存系统的管理决策提供了理论依据。     

补货能力影响部分短缺量拖后率的边补货边需求EOQ模型

Based on the hypothesis of time-dependent partial backlogging,the effect of the waiting time between the next replenishment and the satisfaction of the backlogging demand on the rate of partial backlog-grog was investigated in this paper. Then the backlogging rate influenced by the replenishment capacity and the total of backlogging demand was proposed. Based on this new standpoint,an EOQ model of replenishment with the replenishment capacity affecting the partial backlogging was built up.At last,an emulator was performed and the results showed:improving the replenishment capacity could reduce the replenishment times to a lower constant level;this effect may increase the waiting time before the next replenishment,but it could decrease the waiting time after the start of reple山shment;so the trend of the lostsales varying with the replenishment capacity was not very distinct at the medium level of the replenishment capacity;However,the more adequate replenishment capacity could reduce the number of lostsales and improve the rate of partial backlogging during shortage period than the less one.     

Note on inventory models with Weibull distribution deterioration

This article explores the inventory model with a general demand rate function in which both the Weibull distributed deterioration and partial backlogging are considered. The inventory model discussed here is based on the important finding by Wu [Wu, K.S., 2001. An EOQ inventory model for items with Weibull distribution deterioration, ramp type demand rate and partial backlogging. Production Planning and Control, 12, 787–793]. There are four parts in our research. First, we derive the analytical framework of the inventory model for a general demand rate function1 1.?Based on detailed suggestions of Professor Wafik H. Iskander, Email: whiskander@mail.wvu.edu . Second, for the ramp type demand, we improve Wu's model to find the criterion to guarantee the existence and uniqueness of the optimal solution. Third, we develop a new model to compensate for the missing case in Wu's article. Fourth, we combine our results to show that our findings are applicable to the ramp type demand inventory model, so that the optimal solution is independent of the demand function. Finally, some numerical examples and graphs are provided to illustrate our discovery and demonstrate the application of our analytical framework.     

短缺量拖后率、需求和采购价均为时变的变质物品EOQ模型

基于需求和采购价均为时变的EOQ模型,进一步考虑时变短缺量拖后率以及资金时间价值等因素对变质物品库存管理的影响,建立了相应的EOQ模型。采用Mathematica4 1对模型进行仿真寻优和主要参数的灵敏度分析,结果显示,最优解存在且库存系统的各参数对最优库存控制策略有不同程度的影响。     

Joint pricing and ordering policy for a deteriorating inventory with partial backlogging

In this paper, a deterministic inventory model for deteriorating items with time-dependent backlogging rate is developed. The demand and deterioration rate are known, continuous, and differentiable function of price and time, respectively. Under these general assumptions, we first prove that the optimal replenishment schedule not only exists but is unique, for any given selling price. Next, we show that the total profit is a concave function of price when the replenishment schedule is given. We then provide a simple algorithm to find the optimal selling price and replenishment schedule for the proposed model. Finally, we use a numerical example to illustrate the algorithm.     

Investment in set-up time reduction with time-varying demand

In this paper, a mathematical model is developed to investigate the economic effects of set-up time reduction. In this model, the concept of product life cycle and continuous demand are included, with the objective of minimizing the total relative cost while demand is variable over time. Also, budget constraints are added to describe the conditions of limited investment. Following the suggested procedure of deciding investment in set-up time reduction, a manager can conclude if set-up time reduction is economically feasible and allocate the investment optimally. Finally, an example about the declining market demand is provided to demonstrate the application of the model.     

A quick response production strategy to market demand

The reason for considering the quick response production strategy to market demand is due to the rapid technology change, which results in decreasing market price and obsolescence. This study considers a production strategy of locating final production line in response to the changes in market demand and the continuous deterioration in stock. The demand rate is assumed to decrease exponentially with time while the price is assumed to decrease linearly with time. The purpose of this study is to derive the most economical site of final-production line that assembles products with short life cycle. The model considered in this research takes into account the sales revenue, the deteriorating cost, the carrying cost, the variable cost and the fixed cost of production. Although there is a higher labour and material cost when the production site is located near market point, the total profit increases due to quicker responsive time, smaller import tax, lower inventory and lesser deteriorating cost.     

An optimal replenishment model for inventory items with normally distributed deterioration

This paper deals with the inventory replenishment problem for deteriorating items with normally distributed shelf life, continuous time-varying demand, and shortages under the inflationary and time discounting environment. The reasons of choosing normal are twofold: it is one of the most important probability phenomena in the real world due to the classical central limit theorem, and it is also one of the most commonly used lifetime distributions in reliability contexts. The problem is formulated as a dynamic programming model and solved by numerical search techniques. The solutions of the model determine the optimal replenishment schedule over a finite planning horizon so that the present worth of the future costs associated with the system is minimized. In the extensive experiments, we validate the model, demonstrate the optimal replenishment schedule and lot-size, and carry out a comparative study to ascertain its contribution. In addition, sensitivity analysis was provided to help identify the most crucial factors that affect system performance. The experimental result shows that the deteriorating problem solved by an appropriate model (i.e. the proposed normal model) can save the total cost up to 2% approximately. It also identifies that the magnitudes of purchase cost per unit and demand rate are the most significant parameters that affect the replenishment decisions and cost.     

OPTIMALITY OF STATE-DEPENDENT (s,S) POLICIES IN INVENTORY MODELS WITH MARKOV-MODULATED DEMAND AND LOST SALES

Markov-modulated processes have been used in stochastic inventory models with setup costs for modeling demand under the influence of uncertain environmental factors, such as fluctuating economic and market conditions. The analyses of these models have been carried out in the literature only under the assumption that unsatisfied demand is fully backlogged. The lost sales situation occurs in many retail establishments such as department stores and supermarkets. We use the analysis of the Markovian demand model with backlogging to analyze the lost sales case; in particular, we establish the optimality of an (s, S)-type policy under fairly general conditions.     

Economic ordering policy of deteriorated item for vendor and buyer: An integrated approach

This study develops an economic ordering policy of a deteriorating item with a constant production and demand rate. By considering the view of both the vendor and buyer, a mathematical model subject to single-vendor-single-buyer and multiple deliveries per order is developed. It can be shown that the integrated approach results in an impressive cost-reduction compared with an independent decision by the buyer.     

A partial backordering approach to inventory control

We study the effects of using a partial backordering approach to controlling inventories under deterministic and stochastic demands, respectively. With a deterministic demand, our model is built with the objective of minimizing the total cost of ordering, holding, backordering and lost sales. The conditions for the partial backordering policy to be feasible are identified and a pair-wise comparison among the no-backordering, complete backordering, and partial backordering doctrines is conducted. In the stochastic case, we focus on a make-to-stock system with a Poisson demand and exponential production time, which allows us to establish a queuing model to examine the cost-effectiveness of using partial backorders. The conditions under which the partial backordering policy outperforms the complete backordering policy are identified.     

An arborescent inventory model in a supply chain system

This study develops an arborescent (tree-like) inventory model with a constant demand rate. By considering the integration of the producer, distributors and retailers, a mathematical model and an economic ordering policy are developed. It can be shown that the integrated approach results in an impressive cost-reduction compared with an independent decision by the partial party. A numerical example of an arborescent inventory system is attached to demonstrate the economic ordering policy with the help of mathematical software - Maple V.     

Distributionally Robust Optimization of Two‐Stage Lot‐Sizing Problems

This paper studies two‐stage lot‐sizing problems with uncertain demand, where lost sales, backlogging and no backlogging are all considered. To handle the ambiguity in the probability distribution of demand, distributionally robust models are established only based on mean‐covariance information about the distribution. Based on shortest path reformulations of lot‐sizing problems, we prove that robust solutions can be obtained by solving mixed 0‐1 conic quadratic programs (CQPs) with mean‐risk objective functions. An exact parametric optimization method is proposed by further reformulating the mixed 0‐1 CQPs as single‐parameter quadratic shortest path problems. Rather than enumerating all potential values of the parameter, which may be the super‐polynomial in the number of decision variables, we propose a branch‐and‐bound‐based interval search method to find the optimal parameter value. Polynomial time algorithms for parametric subproblems with both uncorrelated and partially correlated demand distributions are proposed. Computational results show that the proposed models greatly reduce the system cost variation at the cost of a relative smaller increase in expected system cost, and the proposed parametric optimization method is much more efficient than the CPLEX solver.     

有限时域内部分缺货的变质品生产-定价策略研究

研究有限时域内对变质产品同时安排生产计划和制定定价策略的问题。有限时域被划分成同等长度的多个周期,产品以固定的生产率间歇生产,并以固定的速率发生变质。需求同时依赖于时间和产品价格,在每个周期内都允许缺货且短缺量部分延迟订购。目的是要寻求一个使有限时域内系统的平均利润最大化的生产计划和定价策略。在算例中,分别讨论了需求随时间增大和减小两种不同的需求模式,采用Box复合算法,通过数值计算求得相应的最优生产计划和定价策略。分析表明：对于成长期或销售季初的产品,系统应采用“小批量多批次”的生产方式;而对于衰退期或销售季末的产品,应采用“大批量小批次”的生产方式。此外,不同类型的产品在不同需求模式下的定价策略有所不同：对于有限时域较短或变质率较高的产品,处于衰退期或销售季末的定价要低于成长期或销售季初的定价;相反,对于有限时域相对较长或变质率较低的产品,在衰退期或销售季末的最优定价要高于在成长期或销售季初的定价。     

Inventory Rationing for Multiple Class Demand under Continuous Review

We consider how a firm should ration inventory to multiple classes in a stochastic demand environment with partial, class‐dependent backlogging where the firm incurs a fixed setup cost when ordering from its supplier. We present an infinite‐horizon, average cost criterion Markov decision problem formulation for the case with zero lead times. We provide an algorithm that determines the optimal rationing policy, and show how to find the optimal base‐stock reorder policy. Numerical studies indicate that the optimal policy is similar to that given by the equivalent deterministic problem and relies on tracking both the current inventory and the rate that backorder costs are accumulating. Our study of the case of non‐zero lead time shows that a heuristic combining the optimal, zero lead time policy with an allocation policy based on a single‐period profit management problem is effective.     

An EOQ model with deteriorating items in response to a temporary sale price

In economic order quantity models, it is often assumed that the unit purchase cost is constant. Such an assumption is usually not fulfilled in many practical situations. In practice, it is observed that suppliers sometimes offer temporary price discounts to stimulate demand, boost market share or decrease inventories of certain items. In this paper, a deteriorating inventory model with a temporary sale price has been developed. We shall be concerned with finding the optimal total cost saving for deteriorating items during the special replenishment period. Numerical examples are presented to illustrate the proposed model.     

Comparing reactive Kanban and reactive CONWIP

This paper compares a reactive Kanban system to a reactive CONWIP system under conditions of unstable changes in demand using simulation experiments. After an introduction, a model of the JIT ordering systems, the Kanban and the CONWIP systems, is constructed. In order to obtain the fundamental information for developing a control rule of buffer size, the performance of the two types of the JIT ordering systems is analysed under various stable-demand conditions by simulation experiments. Based on the results, the reactive JIT ordering systems are proposed, and the performance of the proposed systems is investigated. The results showed that both of the proposed systems can react to unstable changes in demand and maintain the mean waiting time of demand at less than the required level. In the reactive Kanban system, the total of the mean work-in-process inventories becomes much less than that in the traditional Kanban system without controlling buffer size. However, in the reactive CONWIP system, the total of the mean work-in-process inventories becomes much more than or nearly equal to that in the traditional CONWIP system without controlling buffer size under the strongly correlated or the weakly correlated processing times, respectively. Based on the results, it can be claimed that, in the proposed systems, the reactive Kanban system is more effective to react to unstable changes in demand than the reactive CONWIP system.     

The permutation flow shop problem with just in time production considerations

This research presents a variation to the permutation flow shop problem where Just In Time (JIT) production requirements are taken into account. The model developed in this research employs dual objectives. In addition to the traditional objective of minimizing the production makespan, minimization of Miltenburg's material usage rate is also incorporated. In this model, multiple units of any product are permitted in the production sequence. However, the minimization of material usage rates attempts to prevent batch scheduling of products and allows unit flow of products as required in demand flow manufacturing. A solution method is proposed for determining an optimal production sequence via an efficient frontier approach and Simulated Annealing (SA). Test problems and specific performance criteria are used to assess the solutions generated by the proposed method. Experimental results presented in this paper show that the use of the efficient frontier and SA provide solutions that approach the optimal solution for the performance measures used in this research.     

The impact of distributions of uncertain lumpy demand on inventories

Most studies on inventory management under demand uncertainty analyse the detrimental effects of demand variability (i.e. its coefficient of variation). In contrast, the consequences of the shape of demand distribution (e.g. its multi-modality and asymmetry) have received only minor attention. The aim of the present paper is to assess the impact of the shape of demand distribution on inventories. In particular, it considers contexts in which demand distributions have more than one 'mode' and are asymmetric, thus making requirements lumpy. The analysis is based on a simulation model which, in order to ensure comparable conditions, keeps all the other factors constant (i.e. ceteris paribus), and compares different demand distributions with the same mean and coefficient of variation. Results show that that demand shape is a key driver of inventory investment. Specifically: (i) the magnitude of the impact of multi-modality and asymmetry is comparable to that of variability; (ii) multi-modality and asymmetry can have either a negative or positive effect depending on the target service level sought. The managerial implications of these findings are addressed in the conclusions.     

Postponement implementation in integrated production and inventory plan under deterioration effects: a case study of a juice producer with limited storage capacity

Abstract

The aim of this study is to develop a production and inventory plan for a fresh apple juice producer. During harvest season, the producer extracts premium juice from freshly picked apples and keeps an inventory of these premium apples in his temperature-controlled storage facility. The producer extracts also regular juice from regular apples purchased from third-party storages. To satisfy future demand, the producer carries inventories of juice and apple. The levels of apple inventories are constrained by the producer’s limited storage space, but he can replenish regular apples. To assist the producer in facing demand uncertainty and deterioration of apples, we develop a production and inventory plan that incorporates postponement to mitigate demand uncertainty. As postponement decisions are shaped by the cost structure of inventories, we integrate in one model the postponement decisions and the deterioration mitigation decisions that can alter the inventory costs. We build multi-period stochastic programming with recourse model to determine juice batch sizes and apple inventories that maximize the producer’s expected profit. The optimal solution illustrates the use of time and form postponements. We discuss the interactions between postponement implementation and decisions to mitigate apples deterioration. We compare the production and inventory plans with and without postponement and with and without apple deterioration. We also present sensitivity analyses for the plan under varying inventory cost and storage space.