资金约束下的双物料库存决策优化

通过构建库存优化模型,提出一个基于供应商资金短缺前提下采购两种原材料的最优采购策略。首先利用库存水平和初始资金联合决策求解模型,得到在某一特定库存水平之内只需采购易腐原材料,在该库存水平之外需采购两种原材料的采购策略,且两种情况均考虑资金约束情形。然后在拓展中将单周期库存融资决策延伸到多周期动态库存决策。最后运用控制变量法解决决策过程中涉及到的各种成本参数和采购策略的关系。通过算例验证模型和结论的合理性。     

电子商务环境下两级供应链库存管理决策研究

本文利用order up to level策略建立需求不确定时两级供应链供应商的库存策略模型并进行参数求解,给出最优库存水平以及管理绩效考核指标的求解方法。并通过实例计算,给出电子商务环境下基于两级供应链的供应商库存最优解决方案,提出随着零售商需求波动程度、库存水准的变动,对于供应商最优库存水平、库存成本、缺货成本的相应策略。     

基于协调成本的联合采购参与意愿分析

为了了解两个需求量不同的制造商参与联合采购的意愿,通过寻找他们在不同采购及库存管理政策下的经济订货批量(EOQ)及对应库存相关成本,得出存在协调成本下各制造商愿意进行联合采购的条件.研究结果表明,联合采购及联合库存管理可以降低制造商各自成本,并且需求量小的制造商对联合采购具有更大的热情,同时指出需要进一步完善成本分摊机制.文中对此给出算例进行了说明.     

价格不确定情形的原材料滚动采购策略模型

针对价格不确定情形的原材料采购问题,描述了原材料滚动采购策略的基本思想,在此基础上,针对原材料采购计划周期的每个采购时刻点,在未来多期原材料价格预测结果的基础上,综合考虑原材料成本、一次性采购费用和库存费用,构建了使采购综合成本最小的多阶段最优采购模型,并通过模型求解可确定当期的原材料最优采购量。通过B公司原材料镍采购的实例分析说明了给出采购策略模型的可行性和有效性。     

模糊需求下可单向替代的有机农产品订购策略

针对有机农产品易耗损、供应风险高以及补货困难的问题,建立和比较有机农产品单源采购与存在单向替代的有机和普通农产品双源采购模型,得出不同条件下零售商的最优订购策略和最大期望利润。结果表明,在模糊需求下零售商的最优订购策略不唯一,农产品耗损程度、销售价格、市场需求等都会影响最优策略的选择;当单位农产品所获得的利润小于(大于)未售出所造成的损失时,应该持保守(积极)的采购策略,订购较少(较多)的农产品以避免库存剩余(供应不足);普通农产品的替代效用越大,零售商越倾向选择双源采购策略。     

考虑价格折扣和运输柔性的库存运输优化研究

在考虑运输能力柔性和销售价格折扣的基础上,建立了零售商主导的分散优化模型、供应商主导的分散优化模型和库存运输联合优化模型,分析得出模型的性质。通过比较研究得出不同决策模式下最优策略和系统绩效的关系。研究表明,零售商主导的分散优化模型的库存成本小于运输库存联合优化模型的库存成本;零售商主导的分散优化模型的运输成本大于运输库存联合优化模型的运输成本;运输库存联合优化供应链的总成本小于零售商主导的供应链总成本。     

订单式生产下汽车零配件企业采购决策研究

为解决传统JIT模式下供应链非主导的汽车零配件厂面临的巨大交付压力与高昂存货管理成本问题,基于MTO订单式生产下汽配厂的原材料供应现状,对其原材料进行两步分类得出3类原材料,分别建立以最小化存货成本的多周期动态规划模型,并推出其最优采购策略。最后,采用M企业实际运营数据进行对比分析,发现最优策略下的原材料存货周转天数显著缩短、库存成本显著降低,验证了优化策略的可行性及有效性。     

基于马尔科夫链的双渠道供应链库存优化决策

针对目前双渠道顾客需求不稳定带来的库存控制风险,利用顾客需求转移定性描述顾客需求不稳定,提出基于马尔科夫链的双渠道供应链库存优化模型。考虑双渠道不合作和合作两种情况,应用马尔科夫链方法,分别建立双渠道库存均衡状态概率模型和库存合作转运价格契约模型。通过Matlab算例仿真,分析渠道间顾客转移率对双渠道供应链最优库存策略的影响,得出在两个渠道顾客需求转移时,双渠道供应链合作下的库存策略要优于不合作下的库存策略。     

考虑供应商交货数量风险的订货量分配模型

针对有装配线最小批量要求且供应商交货数量随机条件下的多物料订货量分配问题,以订货成本、采购成本、库存持有成本和拖期成本组成的总成本最小为优化目标,构建了混合整数随机规划模型;使用离散粒子群优化算法对模型进行求解,通过两组算例将粒子群优化算法与遗传算法和枚举算法进行了对比分析,算例结果验证了离散粒子群优化算法解决该问题的可行性和有效性。最后,通过一组实例分析了不同单位拖期成本和单位库存成本情形下的订货量分配方案以及单位拖期成本/单位库存成本这一比例对总成本的影响。实例结果表明,物料的订货量分配方案与单位拖期成本/单位库存成本有关,且总成本与该比例呈线性相关关系。     

可回复多级库存系统的最优订货和回复策略

本文建立的可回复装配多级库存系统由两部分组成：缺陷零部件库存和产成品库存,其中产成品库存既可以通过零件维修、装配来补充,也可以直接从外部采购产成品获得。模型假设产品由两个可回复零件组成,且回收速率和外部需求是稳定的。通过建模和分析,得到了最优外部采购的经济订货批量,以及最佳装配策略和零件存储策略。     

Optimization-based planning for the stochastic lot-scheduling problem

We describe a finite-horizon stochastic optimization model for the stochastic lot-scheduling problem and procedures for finding near-optimal solutions. Several different products are produced by a single-stage process with significant changeover times and costs, and the demand for these products is random. The deterministic version of this problem, the economic lot-scheduling problem, is the subject of a great deal of research. However, the problem with random demand for the products is commonly found in practice but is not as well researched. The models developed in this paper address the problem of dynamically planning the timing and size of production runs in this kind of production environment. We also report some computational results that indicate the quality of the resulting production schedules.     

Purchasing Policy of New Containers Considering the Random Returns of Previously Issued Containers

A number of organizations sell products in containers that can be reused. The time from issue to return of an individual container is usually not known with certainty and there is a chance that the container is never returned (because of loss or irrepairable damage). Consequently, even under a level demand pattern new containers must be acquired from time to time. In this paper a purchasing policy of these new containers is determined for a finite time horizon so as to minimize the total purchasing and expected carrying costs under a prescribed service level. The associated stochastic model is reduced to a deterministic, dynamic lot-sizing problem with possible occurrence of negative net demand (demand minus return). A transformation into the usual nonnegative demand case allows us to apply well-known deterministic lot-sizing procedures to obtain the solution.     

A stochastic production planning model under uncertain seasonal demand and market growth

This paper proposes a stochastic production planning model for an international enclosure manufacturing company with seasonal demand and market growth uncertainty. The company purchases material and subassembly from overseas and long lead times have been observed. To prevent excess inventory and stockout, the company is required to forecast its demand and project its purchasing decisions and production load to its key suppliers in an effort to reduce risks for both parties. To assist purchasing and production decisions, a two-stage stochastic production planning model that explicitly includes uncertainty is developed with the goal of minimising the total production, inventory, and overtime costs under all scenarios. The model is solved using real data from the company and results have demonstrated the effectiveness of the model compared with various deterministic models. Parametric analyses are performed to derive managerial insights related to issues such as overtime usage, inventory holding costs and the proper selection of scenarios under pessimist, neutral, and optimist outlooks. The model has been implemented and an annual saving of more than $400,000 in inventory cost has been achieved.     

Improved forward buying of commodity materials

This research presents the Enhanced Commodity Forward Buy (ECFB) heuristic, a new method for commodity purchasing, which allows strategic forward buying of commodities for products that include commodity components or materials. The ECFB addresses limitations of existing methods by considering stochastic demand and stochastic commodity prices for products that contain both commodity and non-commodity materials. We conduct a simulation test of the new heuristic on 10 commodity indices using actual historical market prices, over a range of holding costs, markup margins, commodity percentages of the product’s cost of goods sold and demand distributions. The results of the simulation show that compared with five other buying methods, the ECFB heuristic’s ability to adapt to variations in both demand and commodity prices allows it to generate higher profits when demand is uncertain and commodity prices are volatile.     

需求信息部分已知下生鲜品的低碳订购策略研究

为了研究需求信息缺失和低碳减排下的生鲜品企业运营决策问题,基于单周期随机库存系统,分别建立受碳限额与交易政策规制和无碳约束的分布式鲁棒优化模型,通过极大极小期望利润准则和最优化方法求解出两种情形下生鲜品的最优订购量,并运用数值算例检验需求随机因子的标准差系数和碳排放权交易价格对生鲜品订购量、利润和碳排放的影响。结果表明,存在唯一的最优库存因子使得生鲜品企业在最坏分布下的期望利润取得最大;与不受碳政策规制情形相比,生鲜品企业在碳限额与交易政策下能够实现高利润和低排放;需求信息缺失对生鲜品企业在碳限额与交易政策下期望利润的影响小于不受碳政策规制情形。     

考虑风险规避行为的弹性供应链网络集成优化

基于前景理论对多维风险环境下的弹性供应链网络设计和运作集成优化问题进行了研究,使用了能够反映决策者风险规避行为特征的效用函数,通过随机情境生成技术模拟多维风险环境,并使用非线性缺货惩罚成本限制缺货量,从而确保供应链网络具有应对多维风险环境的弹性,在此基础上建立多周期非线性混合整数随机规划模型。文中给出了模型求解的线性转化方法与求解算法,并通过具体的数值算例与灵敏度分析验证了优化模型的有效性与实际应用价值。     

Thermoeconomic optimization of a single effect water/LiBr vapour absorption refrigeration system

In this paper, the thermoeconomic theory is applied to the economic optimization of a single effect water/LiBr vapour absorption refrigeration system for air-conditioning application, aimed at minimizing its overall operation and amortization cost. The mathematical and numerical techniques based optimization of thermal system is not always possible due to plant complexities. Therefore, a simplified cost minimization methodology is applied to evaluate the economic costs of all the internal flows and products of the system by formulating exergoeconomic cost equations. Once these costs are determined, the system is thermoeconomically evaluated to identify the effects of design variables on costs and enables to suggest values of design variables that would make the overall system cost effective. Finally, an approximate optimum design configuration is obtained by means of sequential local optimization of the system, carried out unit by unit. The result compares this optimum with the base case and shows percentage variations in the system's operation and amortization cost.     

Setting procurement safety lead-times for assembly systems

This paper describes a practical method for setting safety lead-times for purchased components in assembly systems with uncertainty in the supply process. The approach is specifically designed to be used in an MRP procurement environment. A two-stage production model in which suppliers were uncapacitated with stochastic lead times was developed. Then, a combinatorial optimization method that took advantage of structural properties was developed to produce an optimal integer solution of safety lead-times. In addition to yielding a practical lead-time setting tool, the model led to some interesting policy insights: (1) the flexibility achieved by bringing parts in early may have value even in situations with ideal suppliers; (2) purchasing components in batches offers some of the same protection as does safety lead time, but is less precise and subsequently more expensive; and (3) ignoring the complicating issues of MRP procurement results in far from optimal results.     

从MYDOOB设计谈构建产品的情趣符号

自从工业革命以来,对于功能和形式之间关系的争论就从来没有停止过,是形式追随功能还是功能追随形式似乎是产品设计永远无法得到绝对答案的问题。然而随着文明的不断演进,今天,我们已经开始逐渐将视角从产品本身转移到使用者人的身上——“设计的最终目标,是人而不是产品”、只有真正“服务于人,满足于人”的设计才是好的设计。     

Multiproduct Optimal Batch Sizes with In-Process Inventories and Multi Work Centers

In this paper we extend the classical economic batch size model of Camp to situations where a range of products is made to stock and where the products are manufactured in a production shop consisting of a number of work centers of functionally grouped machines. Assuming that the flow times of the batches along the work centers can be modelled as a queueing process, it is shown that the batch sizes influence the batch waiting times in the shop, and the amount of work in process. The cost function to be minimized consists of ordering costs, final inventory holding costs, and work-in-process carrying costs. We show that the cost function is strictly convex and that the optimal batch sizes can be found by means of well-known numerical methods. We present an outline of an iterative procedure in which the batch size optimization procedure is combined with a shop load optimization procedure to achieve a good overall performance. Using a simplified model that assumes that the products are homogeneous in all respects, we also show that there exists an upper limit for the optimal batch size, which is determined by the ordering costs and the work-in-process carrying costs. Finally, we show that not taking into account work-in-process carrying costs may result in substantial errors in both batch size and cost.