基于随机权重多目标遗传算法的多目标动态单元构建方法

考虑多变的市场需求环境下单元生产系统在多个计划期具有多个目标的动态构建决策问题。通过对单元生产构建过程中的总费用、设备负载与能力之间最大偏差以及零部件跨单元移动的总次数3个目标进行权衡,建立了非线性多目标动态单元构建的数学模型。采用自适应小生境技术、惩罚技术、双轮盘赌法和精华选择策略,提出了基于精华保留策略的随机权重多目标遗传算法求解该组合优化问题。结合实例对模型和算法进行了仿真分析,结果显示了算法对解决多目标动态单元构建问题的有效性。     

基于同质设备多台配置的独立生产单元构建决策

单元化生产作为一种较好实现生产柔性与生产效率融合的先进生产方式,在变种变量需求环境下它已被大量生产企业特别是装配式生产企业所采用。生产单元构建问题是单元化生产系统设计的关键问题和首要问题,也是单元化生产研究领域的一个热点。本文研究设备易复制情形下,通过配置多台同质设备来实现生产单元间无物料移动,并保证生产单元间工作量均衡的独立生产单元构建问题。本文在综合考虑换装时间、加工顺序、设备生产能力、产品需求量等多个实际生产要素的基础上,建立了以平均总流程时间和各生产单元总流程时间与平均总流程时间偏差最小为目标的数学模型,并开发了一个启发式算法来求解数学模型,最后通过数值算例验证了模型和算法的有效性。     

面向并行制造的多生产单元协同调度研究

为提升多生产单元制造系统整体效率，在其系统内开展面向并行制造的协同调度研究，在考虑运输、换线等时间的基础上，构建多生产单元并行协同调度模型，采用并行分段协同遗传算法求解；在此基础上，将所研究协同调度方法应用于某复杂机电产品多生产单元制造车间，并与变批量调度与等批量调度比较。研究表明，所提的并行协同调度方法可以显著提升生产单元效率，提高生产单元设备和人员利用率。     

考虑货主选择惯性的班轮运输系统优化模型

基于需求季节波动背景,在考虑货主选择惯性的条件下,以班轮公司收益最大为目标,构建远洋集装箱运输系统优化模型,优化航线网路结构、航线配船,基于需求波动与货主选择惯性特征优化航线网络的调整方案与舱位配置.基于遗传算法提出一种遗传线性规划混合算法.计算结果表明,优化模型能够在考虑运输服务稳定性的要求下,优化班轮运输系统,在提高班轮公司收益的同时,提升货主的服务体验.最后通过分析计算结果,证明了模型的实际意义与可靠性.     

基于分散搜索的多目标动态单元构建方法

研究市场需求变化的情况下生产单元内部配置可调整的多周期多目标动态单元构建方法.考虑单元构建费用、设备利用率和跨单元移动数目,提出了动态单元构建方法的非线性多目标数学规划模型.为有效求解该模型,开发了一种分散搜索算法.该算法利用多样性初始解产生方法、全局判断方法、参考集更新方法和解改进方法等实现了生产单元的动态构建.对大规模的单元构建实例进行仿真分析,通过与基准算法进行比较,验证了模型与算法的有效性.     

不确定环境下两阶段应急供应链网络建模与优化求解

为制订有效的应急供应链网络规划方案,提升应急组织救援效率、实现资源物质合理配置,考虑供应和需求的不确定性,采用多运输方式联合的配送模式,以最小化网络响应时间、成本和碳排为优化目标,构建两阶段应急供应链混合整数规划模型,同时,基于鲁棒优化理论构建可调节鲁棒优化模型,增强网络应对不确定因素的能力,通过线性对偶理论对含不确定参数的约束进行转化;为提升模型的求解效果,提出一种优化布谷鸟搜索（optimize cuckoo search,OCS）算法,引入基准实例,以验证OCS算法求解多目标函数的优越性和适用性;最后,利用武汉新冠疫期期间应急物资配送数据,研究带有不确定参数的应急供应链网络决策问题,并通过敏感性分析证明鲁棒控制系数对不确定扰动的有效抑制作用。     

基于随机需求的供应链产供销计划协同模型研究

考虑随机客户需求,研究从供应商到最终客户的多层供应链网络产供销计划协同问题。根据给定的假设条件和问题的分析,首先从系统整体优化的角度,建立带有补偿问题的多周期二级随机规划模型,然后提出了优化-仿真相结合的模型求解策略。最后,给出仿真数据进行算例分析,对比采取协同和异步方式制定产供销计划在总成本方面的差异,分析基于随机需求和确定性平均需求的产供销计划在总成本方面的分布特性,计算结果表明随机需求条件下的产供销计划协同模型一方面可以显著缩减供应链总成本,另一方面可以有效控制原材料采购量、产品产量和发货量,减少库存,从而降低客户需求波动带来的市场风险。     

基于多元随机波动模型的信用风险衍生定价

本文将随机波动期权定价封闭解模型扩展到多资产分析框架下.在考虑Cox-Rose模型多资产模拟以及随机波动矩阵的Wishart动态过程的基础上,将风险升水引入收益率方程,并将Merton模型下的公司违约风险扩展到随机分析框架下.最后利用数值模拟技术,对多资产随机分析模型的适用性及解的稳定性进行了模拟分析.其结果表明,多元随机波动模型对违约风险随机发生条件下的公司信用过程具有较之单元确定性模型更强的解释力.利用多资产模型,有助于金融机构更深入地把握企业信用体系中资产价值和负债的动态联动关系,对金融机构的信用风险管理具有十分重要的意义.     

基于改进分层博弈交叉效率模型的政策评价

政策评估作为政策实施过程中的关键环节,是检验政策效果的基本途径与实现资源优化配置的重要依据.在复杂博弈情境下,决策单元群体间竞合关系不变的假设已经不能满足现实中效率评价的需求,考虑群体间动态变化的合作与竞争关系至关重要.本文将外界冲击下主体间竞合关系演变纳入效率评价框架,提出改进分层博弈交叉数据包络分析方法：从公平的视角出发,基于二次目标模型构建多层次效率矩阵,结合Shapley值对决策单元动态关系演变进行效率评价,进而,以水权交易市场试点政策为例,验证该模型的可行性.该方法放松了政策前后群体竞合关系稳定的假设,验证了水权交易市场政策的有效性和外溢性,为能源与环境领域试点政策效果评价提供了新方法.     

基于组织学习的生产系统人人合作方式的仿真研究

为了比较不同的组织合作方式对生产系统绩效的影响,分析了生产系统中组织学习行为和主体合作过程,并基于复杂适应系统理论建立了描述生产系统中生产者的主体模型。在其基础上提出一种集成了主体模型、离散生产系统仿真软件、数据处理软件和应用软件开发环境的人人合作仿真方法。以某摩托车发动机自治生产单元为工程背景,详细给出了基于组织学习的人人合作仿真流程,并以订单完成时间、订单准时完成率、人员利用率及组织学习效应为目标矢量比较分析了指定合作与自主合作对生产系统绩效的不同影响。结果表明,自主合作方式下生产单元的组织柔性较高,更容易应对多品种小批量的混流生产环境。     

农产品流通体系影响农产品价格波动的机理与路径

本文采用规范化实地研究方法，运用质性分析软件对某地农产品批发市场92户嵌入式个案的访谈数据进行分析，较为清晰地阐释了农产品流通体系对农产品价格影响的内在机理及路径。来自实地调查事实证据分析表明，农产品流通体系与农产品价格波动之间具有显著的相关性；且农产品流通体系构成要素通过供求关系、经营成本、心理预期等三个控制因素可以综合影响农产品价格波动及幅度；优化农产品流通体系确实能起到抑制农产品价格过度波动的作用。这说明，短期的农产品生产调控或价格补贴措施对抑制农产品价格过度波动作用有限，建立长效的农产品流通体系内在稳定性以消解体制机制性障碍，比过度偏重生产性调节更重要。     

日本式单元化生产——生产方式在日本的最新发展形态

日本式单元化生产是生产方式在日本的最新发展形态,是在电子等诸多行业被誉为超越精益的一种先进生产方式。我们通过这篇文章对日本式单元化生产做一简要介绍,一方面试图把它引入中国,为中国实现由制造大国向制造强国的转变和制造业的复兴提供一种可供参考的新型生产组织管理模式,另一方面以求引起中国研究者的关注,从而使更多的研究者加入这一生产方式的研究队伍。本文分六个部分,分别概述了日本式单元化生产的起源、产生背景、与传统的欧美式单元化生产的区别、本质特征、实施中的优劣势以及亟待研究的几个关键问题。     

风险质检行为下的模糊生产-库存决策

本文研究在风险质检行为下需求与生产率具有模糊属性的由一个制造商与一个零售商构成的生产-库存问题。在假设制造商生产的产品存在质量缺陷,零售商在质检过程中存在质检风险的基础上,分别建立了需求模糊下的生产-库存总成本模型,需求与生产率模糊下的总成本模型,运用符号距离法进行了逆模糊化处理,将模糊化的生产-库存总成本转化为确定性成本。证明了两类情形下的总成本均是关于最优订购量与最优缺货量的联合凸函数。数值分析结果表明：随着期望缺陷率的增加,最优订购量增加,最优缺货量减少,最优成本增加,且最优成本增加的速度越来越快。一类质检风险增大引起总成本增加,二类质检风险增大引起总成本减少。最优订购策略对质检一类风险敏感,对质检二类风险不敏感。     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

Production control for just-in-time tool-and-die manufacturing

The strategy to implement production control varies in different types of manufacturing systems. We address the issue of production control in unit-based manufacturing systems where the production batch size of the final product is one or two, the product is custom designed and is made up of numerous individual components with similar process routeings lor special machine tools, turbines, boilers, tool-and-die, injection moulding equipment, custom fabrication, etc. We have developed algorithms to generate master production schedules in this particular domain of manufacturing systems using the concept of workgroups. We show how a Kanban-based JIT shopfloor control and purchasing system can be implemented in such systems in tandem with an inventory management system by utilizing the concept of demand lists. We also propose a model for practical implementation of production control in this domain. The methodology is illustrated at a tool-and-die plant where a CIM software is used to apply the JIT-based production control. Preliminary results show a significant reduction in lead times. We try to show the relationship between research and industrial applications of productions of production control and how to bridge the gap between them.     

Product mix in the TFT-LCD industry

As operational costs and equipment depreciation in the TFT-LCD (thin film transistor-liquid crystal display) industry are a high percentage of the total cost, most manufacturers usually fully utilise their production capacity to reduce the average unit cost. However, when the market demand is less than the supply the stock of panels increases; this forces manufacturers to instigate a price war to reduce levels of stock and results in a wide fluctuation in panel prices. Inventory stocks of panels could be decreased by optimising the product mix. This will help manufacturers to reduce the risk of holding stocks, increase profit, and improve competitive advantage. This study uses mixed integer linear programming (MILP) to construct a product mix for the TFT-LCD industry given the conditions of profit, productivity, raw materials supply, and market demand. A case study shows that this model is proven to be effective in generating product mix for the TFT-LCD industry while improving profit. The product mix generated by this model can provide a reference for the sales department for orders and shipping, for the production department for the order quantity, and for master production scheduling for each product.     

随机需求环境下联产品系统价格与产量决策研究

基于固定比例生产技术和多产品随机需求的情形,研究了联产品制造商的两阶段产量和价格联合优化模型。通过反向倒推的优化求解,得到了联产品制造商的最优产量和价格决策以及变化规律。同时研究了需求服从均匀分布时,需求波动对均衡的影响。研究结果表明,在订货成本较低和一种产品的需求波动性较大时,当另外一种产品的波动增大,则该产品的最优订货量增大,同时价格下降。借助数值仿真,分析了价格敏感度和产出比例对最优决策和利润的影响。结果表明,在给定一种产品的价格敏感度时,另外一种的价格敏感度越大,那么该产品的价格就越低,制造商的订货量就下降。当一种产品的产出比例固定时,另一种产品的产出比例上升时,则该产品的价格下降,制造商的订货量下降,总利润上升。     

STOCK LEVELS AND DELIVERY RATES IN VENDORMANAGED INVENTORY PROGRAMS

Using the latest information technology, powerful retailers like Wal‐Mart have taken the lead in forging shorter replenishment‐cycles, automated supply systems with suppliers. With the objective to reduce cost, these retailers are directing suppliers to take full responsibility for managing stocks and deliveries. Suppliers' performance is measured according to how often inventory is shipped to the retailer, and how often customers are unable to purchase the product because it is out of stock. This emerging trend also implies that suppliers are absorbing a large part of the inventory and delivery costs and, therefore, must plan delivery programs including delivery frequency to ensure that the inherent costs are minimized. With the idea to incorporate this shift in focus, this paper looks at the problem facing the supplier who wants quicker replenishment at lower cost. In particular, we present a model that seeks the best trade‐off among inventory investment, delivery rates, and permitting shortages to occur, given some random demand pattern for the product. The process generating demand consists of two components: one is deterministic and the other is random. The random part is assumed to follow a compound Poisson process. Furthermore, we assume that the supplier may fail to meet uniform shipping schedules, and, therefore, uncertainty is present in delivery times. The solution to this transportationinventory problem requires determining jointly delivery rates and stock levels that will minimize transportation, inventory, and shortage costs. Several numerical results are presented to give a feel of the optimal policy's general behavior.     

Design of Stockless Production Systems

In make‐to‐stock production systems finished goods are produced in anticipation of demand. By contrast, in stockless production systems finished goods are not produced until demand is observed. In this study we investigate the problem of designing a multi‐item manufacturing system, where there is both demand‐ and production‐related uncertainty, so that stockless operation will be optimal for all items. For the problem of interest, we focus on gaining an understanding of the effect of two design variables: (i) manufacturing speed—measured by the average manufacturing rate or, equivalently, the average unit manufacturing time, and (ii) manufacturing consistency—measured by the variation in unit manufacturing times. We establish conditions on these two variables that decision makers can use to design stockless production systems. Managerial implications of the conditions are also discussed.