基于应急救援物资单向转运的受灾点库存策略研究

了研究应急救援物流中存在物资单向转运条件下的受灾点库存策略,考虑由多个受灾点组成的单阶段系统,
各个受灾点之间存在单向转运.首先在各个受灾点物资进货点一定条件下,建立模型确定各个受灾点救援物资
需求依靠从其它受灾点转运得到满足的比例和直接从本身库存中得到满足的比例;其次,建立各个受灾点
救援物资进货水平优化的整数非线性规划模型,并考虑基于时间窗的救援效率水平约束,设计基于隐含
枚举法的模型求解算法;最后,运用算例对模型及其求解算法进行了模拟运算,从而验证了模型的有效性和实用性.     

基于改进模拟退火算法的推动式生产-配送协调优化

为减小物资生产与配送不协调造成的成本及生产资源浪费,建立了考虑推动式生产调度的物资配送优化模型,并针对标准模拟退火算法受随机因素影响易陷入局部最优的缺点,设计带有回火与缓冷操作的改进模拟退火算法对模型求解,确定了优化的车辆配送路线以及物资生产计划。对比实验结果表明：相对于单纯的物资配送优化模型,考虑推动式生产调度的配送优化模型,能够有效减小物资滞留时间以及配送延误成本;相较于标准模拟退火算法,改进算法搜索到了更优解,且计算结果的标准差减小了93.42%,稳定性更好;同时,改进模拟退火算法具有较低的偏差率,在中小规模算例中求解质量较高,平均偏差率在0.5%以内。     

整批间隔进货的存储量控制模型与随机局部弹性

利用作者于文[1，2]引入的随机弹性理论，研究了整批间隔进货并不允许缺货的随机存储模型中，一个采购周期内的总费用对最高存储量的弹性．给出了总费用弹性概率密度函数的一般表达式．进一步给出了存在多种需求物资的随机存储模型中总费用对单个物资采购量的弹性分布函数和概率密度函数，讨论了随着采购量的随机变化，总费用的弹性变化规律和变化范围．通过实例研究了当最高库存量的分布特性已知且采购量服从某一分布时，总费用的弹性变化范围及在该变化范围的可信度．     

面向大规模定制的建筑工业化住宅混合装配线平衡优化研究

为解决大规模定制工业化住宅混合装配线平衡问题,以预制构件均匀消耗为目标建立了混合装配线生产优化模型,并基于目标追随法(GCA)和建筑工业化住宅的建造特点,提出相应的求解算法.通过所构建的优化模型及算法,可对随机输入的工业化装配顺序进行优化,进而获得预制构件消耗速率均匀的优化装配顺序.最后,通过案例分析验证了优化模型的有效性,优化结果表明优化后的生产序列的预制构件消耗更为趋近于平均消耗水平,能够获得更为均匀的预制构件消耗速率,进而提升工业化住宅项目的准时性及效率.     

基于两阶段混合整数规划模型的洪涝灾害应急管理研究

本文以洪涝自然灾害为现实背景, 考虑多种应急物资、灾情的不确定性和应急救灾的多目标性, 集成优化灾前准备和灾后响应两阶段, 建立了一定最大救援时间下的两阶段多目标混合整数规划模型。模型的目标一是使得不同灾害情景下灾后响应阶段总物资不足惩罚和延误损失的期望最小, 目标二是使得灾前准备阶段应急物资存储点建造成本、物资存储成本及灾后响应阶段物资分配成本之和最小。该模型保证了应急救灾的及时有效以及物资的公平分配。本文设计了一种多目标遗传算法用于模型求解, 结合具体算例, 得到了模型在最大救援时间为4到9区间内任意数值下的pareto最优解, 很好地适应了决策者不同的决策需求, 并根据pareto应急方案的数目, 灾后响应阶段成本期望和两阶段总成本等模型的三个关键产出随最大救援时间的变化趋势, 得出最优的最大救援时间为5.7。     

基于柔性契约的政府应急物资采购模型研究

面对突发事件导致的巨大物资需求,实物储备往往体现出应对能力不足。而对于生产时间较短的重要应急物资,生产能力储备是缓解这一压力的有效途径。对此,本研究构建了一个物资企业双储备形式下的应急物资采购模型,分析研究了在物资企业可以选择生产形式(常规生产和加急生产)的情况下,政府的最优支付决策和物资企业的双储备决策。推导分析结果显示,物资企业的生产能力约束和政府的支付水平对政企合作形式起到决定性作用。本研究进一步通过数值分析验证模型的有效性和契约合作的优势,并讨论了若干重要外生参数对政企最优决策的影响。     

大规模定制模式下基于三角直觉模糊信息的生产指派问题研究

针对大规模定制模式下生产指派面临的模糊不确定性等问题,探讨如何运用三角直觉模糊数构建生产指派模型进而确定最满意的生产指派方案。首先,运用三角直觉模糊数刻画、设计基于顾客个性化需求与企业产出的相对偏差、产品价格与交货期等影响因素的顾客满意度函数和企业利润函数。其次,建立了兼顾企业利润和顾客满意度的调和函数,据此构建了生产指派模型,并证明该模型有可行解和最优解,然后说明模型的求解方法。最后,通过具体实例说明生产指派模型的求解过程及其有效性、合理性。     

区际救援物资中转调度的动态决策模型与算法

考虑灾害救援中灾区对应急物资的持续消耗,研究了区际多品种救援物资的动态中转调度问题.综合考虑各阶段调度费用、运输费用和库存费用总和最小化的救援物资中转调度安排和库存规划,建立了一个区际救援物资中转调度动态决策模型,并设计了一种矩阵编码的协进化遗传算法.最后通过一个算例验证了模型和算法的有效性.     

军需物资调集规划问题的研究

以军需物资调集为背景 ,在系统分析的基础上建立了全局优化问题的数学规划模型 ,并对模型求解进行了研究 ,提出两阶段规划算法 .仿真计算结果表明所建模型的有效性     

基于NSGA-II的应急生产任务多目标优化模型及算法研究

重大突发事件发生后,若灾区的应急物资需求不能通过调用储备得到满足,则应急生产将成为灾区应急物资供应的重要保障手段。本文研究重大突发事件发生后应急物资生产任务的优化问题,重点关注原材料生产能力变化对完成应急生产任务的影响,以应急生产任务完成时间最短、完成成本最低为决策目标,研究了包含多个供应商、多个制造商以及单个受灾点的应急物资生产任务多目标规划模型。运用在求解多目标规划问题时具有众多优势的非支配排序多目标遗传算法(NSGA-II)对模型进行求解。通过算例分析,NSGA-II可以得到较好的Pareto前沿,并且可以根据不同情况给出最优的应急物资生产和原材料保障方案。本文的研究还表明,要想更快完成应急生产任务,需要做好原材料、资金、电力、交通等各种要素的配套保障工作。     

存货论模型的建立

商家进货要有计划 ,进货过多 ,卖不出去 ,造成货物积压 ,库存费增加 ;进货过少 ,供不应求 ,使销量减少 ,影响收益 .如何合理地定期进货 ,使商家获取收益最大 ,本文就存货论模型 ,利用转移概率 ,寻找最佳进货方案 ,为合理进货提供依据 .     

连锁中心店存贮决策模拟系统研究

针对连锁店中心在约束条件下，如何确定各种商品合理存货水平的问题，本文在建立动态规划模型并求解的基础上，利用计算机对市场需求量的仿真，计算选择连锁中心店存贮量最佳决策方案。     

An EOQ model with stock and price sensitive demand

Many business practices show that the presence of a larger quantity of goods displayed may attract more customers than that with a smaller quantity of goods. This phenomenon implies that the demand may have a positive correlative with stock level. Under such a circumstance, a firm should seriously consider its pricing and ordering strategy since the demand for their goods may be affected by their selling prices and inventory level. This paper aims to develop a continuous inventory model for finding the strategy for a firm that sells a seasonal item over a finite planning time. The purpose of this firm is to maximize its expected profit by determining the optimal ordering quantity and price setting/changing strategy. Some sufficient conditions are found for finding the optimal decision rules.     

MRP performance effects due to forecast bias and demand uncertainty

The effects of forecast bias and demand uncertainty in a batch production environment are investigated using an integrated MRP planning and execution test bed. The use of inflated planned lead time and safety stock to compensate for forecast error is evaluated. Analysis is performed in terms of meeting both the MPS due dates and customer delivery requirements. Forecast bias and demand uncertainty are shown to affect MPS and delivery performance quite differently. Results also show that increasing either planned lead times or safety stock is effective in improving delivery performance. If demand uncertainty dominates completion time variability, the use of safety stock will achieve delivery objectives with less finished goods inventory.     

Congruential Inventory Model for Two-Echelon Distribution Systems

Large-scale inventory-distribution systems typically comprise a hierarchy of warehouses that stock goods for distribution to retailers at which demand for these goods originates. This paper develops an inventory model for two-echelon distribution systems under the assumption that the central warehouse and retailers order periodically. Characteristics of the optimal policy are described. An iterative solution procedure is presented to find optimal or near optimal operating-policy variables. Solutions of the model to a large number of test examples show that the model outperforms other existing models in the literature without sacrificing the computation time. Tested against the lower bounds on the optimal average annual variable cost obtained by removing some of the ordering costs, the solutions of the present model are found to be near optimal.     

高原驻训航材有寿件需求预测研究

高原驻训航材保障中,有寿件重要度较高,部队必须携带足够的备件数量来满足任务需要.根据高原驻训条件下航材有寿件需求特点,将有寿件的需求分为到寿更换需求和随机故障消耗产生的需求两部分,分别用数学公式和仿真计算方法进行预测,再将两者结果相加为总需求量.通过实例分析验证,采用工程测算方法可以避免逐一分析器材寿命的繁杂,而单独考...     

Operations planning for a multi-stage kanban system

A multi-stage production line which operates under a just-in-time production philosophy with linear demand is considered here. The first workstation processes the raw materials after receiving them from suppliers, a kanban mechanism between the workstations transports the work-in-process to the succeeding workstation, and after processing them, delivers the finished products to a buyer or a warehouse. The problem is to find optimally the number of raw material orders, kanbans circulated between workstations, finished goods shipments to the buyers, and the batch size for each shipment (lot). A cost function is developed based on the costs incurred due to the raw materials, the work-in-process between workstations, and the finished goods. Optimal number of raw material orders that minimizes the total cost is obtained, which is then used to find the optimal number of kanbans, finished goods shipments, and the batch sizes for shipments. Numerical examples are used to demonstrate the computations of optimal parameters, and to configure the kanban mechanism on a timescale. Several avenues for future research are also indicated.     

Evaluation of three production planning procedures for the use of recipe flexibility

Process industries often obtain their raw materials from mining or agricultural industries. These raw materials usually have variations in quality, which often lead to variations in the recipes used for manufacturing a product. Another reason for varying the recipe is to minimize production costs by using the cheapest materials that still lead to a satisfactory quality in the product. A third reason for using recipe flexibility is that it may occur that at the time of production not all materials for the standard recipe are available. In earlier research we showed under what conditions the use of this type of recipe flexibility should be preferred to the use of high materials stock to avoid materials shortages. We also showed that the use of recipe flexibility to account for material shortages can be justified if the material replenishment leadtime is long, the demand uncertainty is high and the required service level is high. In this paper we assume that these conditions are satisfied and we investigate three different production planning procedures that make use of recipe flexibility to cope with the uncertainty in demand and supply. We assume that the customer order leadtime is much smaller than the material replenishment leadtime, and therefore demand uncertainty is high. The optimal procedure optimizes material use over a planning horizon equal to the material replenishment leadtime, taking into account the customers orders and knowledge of the distribution function of future demand. The deterministic procedure also optimizes the material use over the material replenishment leadtime, but it assumes a deterministic demand level for unknown orders. The simplest, myopic procedure optimizes material use over only the accepted customer orders. These three procedures are investigated via an experimental design of computer simulations of an elementary small scale model of the production planning situation. The results show that the optimal procedure outperforms the other two procedures. Furthermore, for a realistic cost structure in feed industry under certain circumstances the use of the optimal procedure may lead to a 4% increase in profit. However, this improvement must be weighted against the cost incurred by the operational use of this complex procedure. Based on these considerations and the numerical results in this paper, we may expect that for some situations in practice the use of the simplest myopic procedure, optimizing material use only over the available customer orders, will be justified from an overall cost point of view.     

时变需求等量进货情形下集成供应链生产订货策略研究

构建了一个包含原料采购、生产和销售过程的集成供应链模型,研究了由原料、生产商和销售商产品构成的三层库存系统的生产订货问题。在有限的规划期内,销售商每次进货量相同,生产商按照EOQ模型采购原材料。以最小化供应链系统的总运营成本为目标,构建一个混合整数非线性规划模型,寻找销售商最优订货方案和生产商最佳生产策略。首先利用网络优化方法求解生产商的最优生产计划,其次利用定界穷举法寻求销售商最优的订货周期,给出了具体的计算方法和Matlab程序。通过算例分析验证了算法的有效性,并研究了各参数对最小费用及最优解的影响。