多阶段生产系统最优生产批量和原材料订购决策模型

Sarker和Parija(1996)建立了生产系统最优生产批量和原材料订购决策模型。然而他们的模型仅局限于单阶段生产系统,本文将他们的模型扩展到多阶段生产系统,我们首先建立了使整个多阶段生产系统总成本最小的各阶段最优生产批量、原材料订购批量及阶段之间的运输批量模型,然后分析了原材料订购费、半成品运费及设备安装费的敏感性。最后,我们结合实例综合分析了原材料订购费、半成品运输费和设备安装费的变化及最小值点取整后对原材料订购决策、最优生产批量和总成本的影响。     

Optimal policy for brownian inventory models with general convex inventory cost

We study an inventory system in which products are ordered from outside to meet demands, and the cumulative demand is governed by a Brownian motion. Excessive demand is backlogged. We suppose that the shortage and holding costs associated with the inventory are given by a general convex function. The product ordering from outside incurs a linear ordering cost and a setup fee. There is a constant leadtime when placing an order. The optimal policy is established so as to minimize the discounted cost including the inventory cost and ordering cost.     

Optimal spare ordering policy for preventive replacement under cost effectiveness criterion

This paper presents a spare ordering policy for preventive replacement with age-dependent minimal repair and salvage value consideration. The spare unit for replacement is available only by order and the lead-time for delivering the spare due to regular or expedited ordering follows general distributions. To analyze the ordering policy, the failure process is modelled by a non-homogeneous Poisson process. By introducing the costs due to ordering, repairs, replacements and downtime, as well as the salvage value of an un-failed system, the expected cost effectiveness in the long run are derived as a criterion of optimality. It is shown, under certain conditions, there exists a finite and unique optimum ordering time which maximizes the expected cost effectiveness. Finally, numerical examples are given for illustration.     

An efficient algorithm for a generalized joint replenishment problem

In most multi-item inventory systems, the ordering costs consist of a major cost and a minor cost for each item included. Applying for every individual item a cyclic inventory policy, where the cycle length is a multiple of some basic cycle time, reduces the major ordering costs. An efficient algorithm to determine the optimal policy of this type is discussed in this paper. It is shown that this algorithm can be used for deterministic multi-item inventory problems, with general cost rate functions and possibly service level constraints, of which the well-known joint replenishment problem is a special case. Some useful results in determining the optimal control parameters are derived, and worked out for piecewise linear cost rate functions. Numerical results for this case show that the algorithm significantly outperforms other solution methods, both in the quality of the solution and in the running time.     

Integrated vendor–buyer cooperative inventory models with controllable lead time and ordering cost reduction

This study deals with the lead time and ordering cost reduction problem in the single-vendor single-buyer integrated inventory model. We consider that buyer lead time can be shortened at an extra crashing cost which depends on the lead time length to be reduced and the ordering lot size. Additionally, buyer ordering cost can be reduced through further investment. Two models are presented in this study. The first model assumes that the ordering cost reduction has no relation to lead time crashing. The second model assumes that the lead time and ordering cost reduction are interacted. An iterative procedure is developed to find the optimal solution and numerical examples are presented to illustrate the results of the proposed models.     

考虑即时采购价格的物流服务供应链优化

物流服务市场的不确定性会影响物流服务供应链的服务水平和收益。在考虑随机即时采购价格以及基础物流提供商在正常情况和应急情况下具有不同物流能力投资成本的情形下,引入期权机制研究不确定市场环境下物流服务供应链的优化决策,以提高物流服务供应链柔性和降低市场不确定性带来的风险。构建物流服务供应链的期权契约模型,采用Stackelberg博弈理论和优化算法分析和求得物流服务集成商的最优期权采购和即时采购策略,以及基础物流提供商的最优物流能力投资策略。结果表明即时采购价格将影响基础物流提供商和物流服务集成商的决策。最后通过数值分析研究即时采购价格的不确定程度对物流服务集成商和提供商的优化策略和利润的影响。     

The level probabilities for a simple loop ordering

Bartholomew's statistics for testing homogeneity of normal means with ordered alternatives have null distributions which are mixtures of chisquared or beta distributions depending on whether the variances are known or not. The mixing coefficients depend on the sample sizes and the order restriction. If a researcher knows which mean is smallest and which is largest, but does not know how the other means are ordered, then a loop ordering is appropriate. Exact expressions for the mixing coefficients for a loop ordering and arbitrary sample sizes are given for five or fewer populations and approximations are developed for more than five populations. Also, the mixing coefficients for a loop ordering with equal sample sizes are computed. These mixing coefficients also arise in testing the ordering as the null hypothesis, in testing order restrictions in exponential families and in testing order restrictions nonparametrically.This research was supported by the National Institutes of Health under Grant 1 R01 GM42584-01A1     

具有非线性采购成本库存控制问题的研究现状与挑战

库存管理是基于运筹学而发展起来的一门学科,并成为近几十年来运筹学和管理科学重要的研究领域之一。在库存系统中,采购成本是必不可少的成本之一,主要包含产品成本、运输成本、装卸成本等。现实中,采购成本依赖于采购量,且往往是采购量的非线性函数。介绍了几类常见的采购成本函数：依赖于采购量的固定成本、增量折扣、全量折扣、车载容量折扣和凸采购成本等。基于周期盘点库存模型和连续盘点库存模型,综述了带有这些非线性采购成本函数的库存模型研究进展。虽然经过了几十年的研究,但很多带有非线性采购成本的库存模型的最优采购策略因为其复杂性至今未能被完整刻画。通过综述来简单讨论该类问题的挑战和机会。     

An optimal ordering policy for a spare unit with lead time

We consider a generalised ordering policy in which a spare unit for replacement can be delivered only by order after a constant lead time. Introducing the costs for ordering, shortage and holding, we derive the expected cost per unit time in the steady-state. We discuss the optimal ordering policy which minimises the expected cost, and show in a main theorem that the optimal policy is reduced to either one of two typical ordering policies depending on some conditions. We further discuss a similar ordering policy with varying lead times.     

A generalized discrete-time order replacement model

In this article, we consider a discrete-time order replacementproblem. More precisely, we treat a generalized model with morecomplex cost structure than Kaio & Osaki (1979, IEEE Trans.Reliab., R-29, 405–406) and with two decision variables:allowable inventory time and ordering time. Based on the discreteprobabilistic argument, we derive the optimal ordering policyto deliver a spare unit preventively by a regular order, soas to minimize the expected cost per unit time in the steadystate. Numerical examples are devoted to carrying out the sensitivityanalysis of model parameters on the optimal ordering policyand its associated expected cost value.     

Multi-mode resource-constrained project scheduling problem with material ordering under bonus–penalty policies

This study emphasizes that project scheduling and material ordering (time and quantity of an order) must be considered simultaneously to minimize the total cost, as setting the material ordering decisions after the project scheduling phase leads to non-optimal solutions. Hence, this paper mathematically formulates the model for the multi-mode resource-constrained project scheduling with material ordering (MRCPSMO) problem. In order to be more realistic, bonus and penalty policies are included for the project. The objective function of the model consists of four elements: the material holding cost, the material ordering cost, the bonus paid by the client and the cost of delay in the project completion. Since MRCPSMO is NP-hard, the paper proposes three hybrid meta-heuristic algorithms called PSO-GA, GA-GA and SA-GA to obtain near-optimal solutions. In addition, the design of experiments and Taguchi method is used to tune the algorithms’ parameters. The proposed algorithms consist of two components: an outside search, in which the algorithm searches for the best schedule and mode assignment, and the inside search, which determines the time and quantity of orders of the nonrenewable resources. First, a comparison is made for each individual component with the exact or best solutions available in the literature. Then, a set of standard PROGEN test problems is solved by the proposed hybrid algorithms under fixed CPU time. The results reveal that the PSO-GA algorithm outperforms both GA-GA and SA-GA algorithms and provides good solutions in a reasonable time.     

Optimal multiple stage expansion of competence set

In this paper, we consider the expansion processes of competence sets which have asymmetric cost functions, intermediate skills, and compound skills; among the skills, cyclic connections are possible. We introduce the concept of the stage expansion process (SEP) of the competence set, and provide mathematical programming methods to find a minimal cost SEP and the ordering of expansion.     

Optimal spare ordering policy under a rebate warranty

This paper develops, from the customer’s perspective, the optimal spare ordering policy for a non-repairable product with a limited-duration lifetime and under a rebate warranty. The spare unit for replacement is available only by order and the lead time for delivery follows a specified probability distribution. Through evaluation of gains due to the rebate and the costs due to ordering, shortage, and holding, we derive the expected cost per unit time and cost effectiveness in the long run and examine the optimal ordering time by minimizing or maximizing these cost expressions. We show that there exists a unique optimum solution under mild assumptions. We provide a numerical example and illustrate sensitivity analysis.     

Optimal two-stage ordering policy with Bayesian information updating

We investigate in this paper an optimal two-stage ordering policy for seasonal products. Before the selling season, a retailer can place orders for a seasonal product from her supplier at two distinct stages satisfying the lead-time requirement. Market information is collected at the first stage and is used to update the demand forecast at the second stage by using Bayesian approach. The ordering cost at the first stage is known but the ordering cost at the second stage is uncertain. A two-stage dynamic optimization problem is formulated and an optimal policy is derived using dynamic programming. The optimal ordering policy exhibits nice structural properties and can easily be implemented by a computer program. The detailed implementation scheme is proposed. The service level and profit uncertainty level under the optimal policy are discussed. Extensive numerical analyses are carried out to study the performance of the optimal policy.     

Optimal number of minimal repairs before ordering spare for preventive replacement

This paper presents a model for determining the optimal number of minimal repairs before ordering spare for preventive replacement. By introducing the costs of ordering, repair, downtime, replacement, and the salvage value of an un-failed system, the expected long-term cost rates and cost effectiveness are derived. It is shown that, under certain conditions, the optimal number of minimal repairs, which minimizes the cost rate or maximizes the cost effectiveness, is given by a unique solution of an equation. A numerical example is also given for illustration of the proposed model.     

Performance comparisons for maintained items

Most maintenance studies deal with the problem of maintenance-costs optimization, given the cost of the available maintenance actions and a cost objective function. The focus in this paper is on yet another relevant aspect namely the improvement in performance that results from a maintenance action in terms of performance criteria of interest. The evaluation of performance improvement requires comparisons of random quantities which is done by means of suitable probabilistic ordering notions. Different modelling situations are considered, and for each of them conditions are obtained on the life distributions of the present item, and the new one if of different type, that ensure performance improvement. Apart from providing a decision tool for maintenance application, the paper also contributes to clarifying relationships between (probabilistic) ordering notions and aging properties within the maintenance context.     

Truncated Sequential Test for a Proportion and it's Sample Space Ordering Method

This paper proposes a new sampling plan, the sample space ordering method, to compute the optimum truncated sequential test in order to overcome the disadvantages of the widely use sequential sampling methods that IEC1123 has presented. The main ideal of this new method is to establish an order at the truncated sequential sample space, and optimize point by point to arrive the optimal truncated sequential test. The paper presents in detail how to realize the new plan, and shows that this new plan has most powerful to control the sample number and least average sample number comparing with the methods which IEC1123 and SMT have proposed.     

Optimal policy for a two-facility inventory problem with storage constraints and two freight modes

This paper considers a two-facility supply chain for a single product in which facility 1 orders the product from facility 2 and facility 2 orders the product from a supplier in each period. The orders placed by each facility are delivered in two possible nonnegative integer numbers of periods. The difference between them is one period. Random demands in each period arise only at facility 1. There are physical storage constraints at both facilities in each period. The objective of the supply chain is to find an ordering policy that minimizes the expected cost over a finite horizon and the discounted stationary expected cost over an infinite horizon. We characterize the structure of the minimum expected cost and the optimal ordering policy for both the finite and the discounted stationary infinite horizon problems.     

随机需求下基于供应中断的备份供应商决策分析

假定需求服从随机分布,研究由零售商主导的供应链中,采用一个战略供应商和一个备份供应商模式,零售商与备份供应商通过能力期权建立订货契约:首先,零售商向备份供应商预订能力,支付预订成本;接着,向战略供应商订货,如果没有发生突发事件则其供货量等于订货量,否则供货量变为零;然后,零售商基于战略供应商的供货量和备份供应商的能力预订确定向备份供应商的订货量,支付执行成本;最后,零售商用战略供应商和备份供应商的总供货量满足顾客需求。备份供应商在考虑自己的能力维持成本和制造成本后决定是否接受零售商提供的能力期权契约。针对零售商可选择的四种不同策略,求得采取不用策略所满足的条件,并给出相应的最优订货量、能力预订量和能力执行量和最优利润等的解析解。     

Towards a normative model for inventory cost management in a generalized ABC classification system

This paper establishes a general ABC inventory classification system as the foundation for a normative model of the maintenance cost structure and stock turnover characteristics of a large, multi-item inventory system with constant demand. For any specified number of inventory classes, the model allows expression of the overall system combined ordering and holding cost in terms of (i) the re-ordering frequencies for the items in each inventory class and (ii) the inventory class structure, that is, the proportion of the total system's items that are in each inventory class. The model yields a minimum total maintenance cost function, which reflects the effect of class structure on inventory maintenance costs and turnover. If the Pareto curve (a.k.a. Distribution-by-value function) for the inventory system can be expressed (or approximated) analytically, the model can also be used to determine an optimal class structure, as well as an appropriate number of inventory classes. A special case of the model produces a simply structured, class-based ordering policy for minimizing total inventory maintenance costs. Using real data, the cost characteristics of this policy are compared to those of a heuristic, commonly used by managers of multi-item inventory systems. This cost comparison, expressed graphically, underscores the need for normative modelling approaches to the problem of inventory cost management in large, multi-item systems.