时间窗需求下供应商管理库存补货及发货动态批量研究

研究了一个有限计划期内、需求带有时间窗约束的供应商管理库存供应链的补货及发货动态批量问题.考虑了两种发货运输方式,即自营物流运输和采用第三方物流运输,并提出了相应的两种多项式算法寻找供应商最优的补货及发货策略.当采用自营物流运输方式时,假设发货成本是发货量的阶梯函数,且每个时间窗内的需求必须被一次发货批量满足,该问题为NP难题.因此,假设每个时间窗内的需求允许被多次发货批量满足,且时间窗约束结构一致,提出了一种多项式算法寻找供应商最优的补货及发货策略,其计算复杂度为O(T4).当采用TPL运输方式时,发货成本是发货量的线性增函数,且在任意的时间窗约束下,提出了一种复杂度为O(T3)的算法寻找供应商最优的补货及发货策略.     

Optimal inventory policy involving back-order discounts and variable lead time demand

This paper allows the backorder rate as a control variable to widen applications of the Wu and Tsai’s 2001 model. Moreover, we also consider the backorder rate that proposed by combining the work of Ouyang and Chuang 2001 (also see Lee 2005) with the work of Pan and Hsiao 2001, 2005) (also see Pan et al. 2004) to present a new general form. Thus, the backorder rate is dependent on the amount of shortages and backorder price discounts. In addition, we also develop an algorithmic procedure to find the optimal inventory policy. Finally, a numerical example is also given to illustrate the results.     

A heuristic method for the combined location routing and inventory problem

The combined location routing and inventory problem (CLRIP) is used to allocate depots from several potential locations, to schedule vehicles’ routes to meet customers’ demands, and to determine the inventory policy based on the information of customers’ demands, in order to minimize the total system cost. Since finding the optimal solution(s) for this problem is a nonpolynomial (NP) problem, several heuristics for searching local optima have been proposed. However, the solutions for these heuristics are trapped in local optima. Global search heuristic methods, such as tabu search, simulated annealing method, etc., have been known for overcoming the combinatorial problems such as CLRIP, etc. In this paper, the CLRIP is decomposed into two subproblems: depot location-allocation problem, and routing and inventory problem. A heuristic method is proposed to find solutions for CLRIP. First of all, an initial solution for CLRIP is determined. Then a hybrid heuristic combining tabu search with simulated annealing sharing the same tabu list is used to improve the initial solution for each subproblem separately and alternatively. The proposed heuristic method is tested and evaluated via simulation. The results show the proposed heuristic method is better than the existing methods and global search heuristic methods in terms of average system cost.     

A simulation based heuristic for serial inventory systems under fill-rate constraints

We examine the problem of minimizing average inventory costs subject to a fill-rate constraint in a Clark and Scarf type serial inventory model with a normal demand process. We propose a simulation based heuristic procedure to solve this problem. Using a recent result by Sobel [1] that is an exact base-stock level for a single-stage model, the lower bounds of base-stock levels in each stage of the serial system are obtained. Then, through an effective approximate method, the given problem is decomposed into subproblems. Using the convexity of these subproblems, near optimal base-stock levels are determined sequentially from the most upstream stage to the downstream stage. Numerical tests have shown a highly accurate performance of the proposed heuristic.     

Scheduling and replenishment plan for an integrated deteriorating inventory model with stock-dependent selling rate

An integrated approach is used to clarify the critical issues of scheduling and replenishment planning in an advanced inventory system under stock-dependent selling rate environment. This is because integration removes the barriers between enterprises and improves overall performance. A close collaboration such as just-in-time (JIT) operations also improves product quality of the supply chain. Different from the single-stage inventory model, this study develops an integrated two-stage production-inventory deteriorating model for the buyer and the supplier with stock-dependent selling rate, as well as considering imperfect items and JIT multiple deliveries. Our paper proposes a significant method using a time-weighted-inventory approach to analyze the supplier’s saw-tooth holding cost. We derive the optimal number of inspection, optimal deliveries and the optimal delivery-time interval. A numerical example is also presented to illustrate the theory. The results show that the fixed demand rate, the holding cost and the unit inspection cost are critical in the management of the deteriorating inventory model.     

A single-vendor multiple-buyer inventory model with a multiple-shipment policy

This paper presents a new methodology to obtain the joint economic lot size in the case where multiple buyers are demanding one type of item from a single vendor. The shipment policy is found and a new model is proposed to minimise the joint total relevant cost (JTRC) for both vendor and buyer(s). Considering the two-buyer and the more-than-two-buyer cases, an analytical solution and numerical solution are obtained. A significant savings in joint total relevant cost is achieved when the total demand rate is close to the production rate. A sensitivity analysis is also conducted to test the robustness of the new model .     

A genetic algorithm to optimize multiproduct multiconstraint inventory control systems with stochastic replenishment intervals and discount

There are two main assumptions in multiperiodic inventory control problems. The first is the continuous review, where, depending on the inventory level, orders can happen at any time, and the other is the periodic review, where orders can only happen at the beginning of each period. In this paper, these assumptions are relaxed, and the periods between two replenishments are assumed independent and identically distributed random variables. Furthermore, the decision variables are assumed integer-type and that there are two kinds of space and budget constraints. The incremental discounts to purchase products are considered, and a combination of backorder and lost sales are taken into account for the shortages. The model of this problem is shown to be a mixed integer-nonlinear programming type, and in order to solve it, both genetic algorithm and simulated annealing approaches are employed. At the end, two numerical examples are given to demonstrate the applicability of the proposed methodologies in which genetic algorithm method performs better than simulated annealing in terms of objective function values.     

A replenishment policy for perishable products with non-linear holding cost under stochastic supply lead time

The development and application of inventory models for deteriorating items is one of the main concerns of subject matter experts. The inventory models developed in this field have focused mainly on supply chains under the assumption of constant lead time. In this study, we develop an inventory model for a main class of deteriorating items, namely perishable products, under stochastic lead time assumption. The inventory system is modeled as a continuous review system (r, Q). Demand rate per unit time is assumed to be constant over an infinite planning horizon and the shortages could be backordered completely. For modeling the deterioration process, a non-linear holding cost is considered. Taking into account the stochastic lead time as well as a non-linear holding cost makes the mathematical model more complicated. We customize the proposed model for a uniform distribution function that could be tractable to solve optimally by means of an exact approach. We then solve an example taken from the literature to demonstrate the applicability and effectiveness of the proposed model. Finally, by doing several sensitivity analyses for the key parameters of the model, some managerial insights are proposed.     

单制造商-单销售商供应链的多物品联合补货及协调策略

为降低原材料制造商的成本,在同时考虑制造商的原材料固定订购费用、固定生产装配费用和销售商固定订购费用的情况下,研究了由单制造商和单销售商组成的两层供应链的联合补货问题.为揭示企业合作和多物品联合生产补货对供应链各成员及链的总费用的影响,建立了三种生产-补货模型,分析了模型的最优解特性,并给出了搜索算法.最后,给出一个延迟支付协调策略,实现了Pareto改进.     

A generalized measure of bullwhip effect in supply chain with ARMA demand process under various replenishment policies

The measure of bullwhip effect (BWE) has always been a challenging task to the researchers. BWE is one of the main performance measures for a supply chain. In the existing literature, the measurement of BWE has been performed based on the simple demand processes such as Moving Average, AR(1) (AutoRegression), AR(2), Exponential Smoothing and ARMA(1,1) (AutoRegressive Moving Average). In this paper, we have derived generalized expressions of BWE based on the generalized ARMA (p,q) demand process under the various replenishment policies. The expressions have been compared both algebraically and numerically in order to find out the appropriate replenishment policy that leads to minimum valued expression for BWE.     

A heuristic threshold policy for fault detection and diagnosis in multivariate statistical quality control environments

In this paper, a heuristic threshold policy is developed to detect and classify the states of a multivariate quality control system. In this approach, a probability measure called belief is first assigned to the quality characteristics and then the posterior belief of out-of-control characteristics is updated by taking new observations and using a Bayesian rule. If the posterior belief is more than a decision threshold, called minimum acceptable belief determined using a heuristic threshold policy, then the corresponding quality characteristic is classified out-of-control. Besides using a different approach, the main difference between the current research and previous works is that the current work develops a novel heuristic threshold policy, in which in order to save sampling cost and time or when these factors are constrained, the number of the data gathering stages is assumed limited. A numerical example along with some simulation experiments is given at the end to demonstrate the application of the proposed methodology and to evaluate its performances in different scenarios of mean shifts.     

A simulation approach for production-distribution planning with consideration given to replenishment policies

One of the key issues in the current research area of supply-chain networks is a production-distribution plan taking into account a multi-facility, multi-product, and multi-period problem. The purpose of this study is to determine the optimal production-distribution plan in a network with a bill of material (BOM). First, we present a mathematical model to determine the capacities of facilities including the manufacturing plant and distribution center (DC). Next, with consideration given to the uncertainty and complexity of solving such a network, we apply a simulation approach. The simulation model is developed to analyze a production-distribution plan that satisfies customer demands for higher customer satisfaction and lower total relevant costs, while taking replenishment policies into consideration . The computational results for a simple example of the network represent the developed mathematical and simulation model and show the prospects of using this approach. The multi-factor analysis of variance (ANOVA) test results clearly indicate that all three factors have a significant effect on the grouping output.     

Deriving the cost function for a class of three-echelon inventory system with N-retailers and one-for-one ordering policy

A three-echelon inventory system with two warehouses and N-retailers is considered in this paper. Transportation times are constant and retailers face independent Poisson demand. Replenishments are one-for-one. The lead time of a retailer is determined not only by the constant transportation time but also by the random delay incurred due to the availability of stock at the warehouses. Axsäter [2] evaluated the value of the expected two-echelon inventory system cost with the same assumptions, but in this paper, we add a warehouse as third echelon and therefore this may lead to having one more delay in shipment which was incurred in the new warehouse. We obtained the cost function for the inventory system and tested it by several examples.     

Determination of the economical policy of a three-echelon inventory system with (R, Q) ordering policy and information sharing

In this work, we consider a three-echelon serial inventory system with two warehouses (suppliers) and one retailer with information exchange. The retailer applies continuous review (R, Q) policy. The warehouses have online information on the inventory position and demand activities of the retailer. We present a new ordering policy to share information among inventory echelons. The warehouse I and II start with m ₁ and m ₂ initial batches of the same order size of the retailer, respectively. The warehouse I places an order to an outside source immediately after the retailer’s inventory position reaches an amount equal to the retailer’s order point plus a fixed value s ₁, and the warehouse II places an order to the warehouse I immediately after the retailer’s inventory position reaches an amount equal to the retailer’s order point plus a fixed value s ₂. Transportation times are constant and the retailer faces independent Poisson demand. The lead times of the retailer and the warehouse II are determined not only by the constant transportation time but also by the random delay incurred due to the availability of stock at the warehouses. In this paper using the idea of the one-for-one policy, we implicitly incorporate the distribution function of the random delay to obtain the exact value of the expected inventory system cost. Resorting some numerical examples in three different scenarios, we show how information sharing reduces the inventory costs.     

A polynomial time algorithm for production planning with bounded inventory

In petrochemical manufacturing, food processing, glass manufacturing, etc., there is a situation where the production planning is subject to the limit of inventory capacity (or bounded inventory) rather than production capacity. Only a few studies can be found in the literature for this situation. In this paper, the production planning problem with bounded inventory is discussed. Specifically, the problem considered had the following features: (i) backlogging is not allowed, (ii) lost sale is allowed, (iii) the lost sale cost function is time varying and non-increasing, and (iv) inventory capacity is non-decreasing. An algorithm for this problem with the polynomial O(T ³) time complexity is proposed. Though the complexity of the algorithm is the same as that of the other work, see Sandbothe and Thompson (Oper Res 38(3):474–486, 1990), the problem in the other’s work problem is less complex than ours; for instance only a fixed cost function is considered. A case study taken from a real-life production line is provided to further justify the application of the lost sale strategy, demonstrating the effectiveness of our model and algorithm.     

A pattern recognition technique for the analysis of grain boundary structure by HREM

A pattern recognition technique for the detection of structural units in high resolution images of interfaces is described. The technique uses cross-correlation functions as a means of locating atomic patterns characteristic for an interface and as a measure of similarity between related units. Application is not limited to periodic, or even to planar interfaces. Characteristic structural units can be extracted from an experimental image and some important parameters such as mirror or mirror glide symmetry, and rigid body displacements can be determined without knowledge of the imaging parameters. The technique allows an image of a structural unit with reduced specimen noise to be obtained by averaging over several similar units, even if a boundary is not periodic and not planar.     

一种基于棋盘格的高精度分区域相机标定方法

在视觉测量系统中,相机的标定精度至关重要,将影响整个测量系统的精度。针对现有相机标定方法难以兼顾精度和操作复杂度的问题,本文提出了一种基于棋盘格的高精度分区域相机标定方法。首先,将棋盘格置于不同位置,提取不同位置角点的世界坐标和像素坐标,对所有角点用线性变换和非线性最优算法求解出全局标定参数。然后,将角点分为中间区域角点和边缘区域角点,对两区域角点分别标定得到两组分区域标定参数。标定实验结果表明：与全局标定法相比,分区域标定法的图像平均投影误差至少降低16%。该方法操作简单,精度高,可以很好的应用于工业视觉检测。