随机生产服务系统最优服务能力分配策略

针对由生产设施和服务中心组成的柔性生产服务系统,研究服务能力在不同订单之间的分配问题。生产设施生产两类产品,服务中心基于对应的产品为两类顾客提供不同的服务,服务每个顾客订单需要消耗对应的产品。生产和服务时间均服从指数分布,需求过程为泊松过程。因服务能力有限,管理者在任何时刻须决定将服务能力分配给哪一类订单。将系统的最优服务能力分配问题转化为一个连续时间马尔科夫决策过程。通过解析证明和分析,发现该随机系统的最优服务策略为形式非常简洁的指标型优先权服务策略,但又不同于传统服务系统的最优服务策略。最后,分别对最优服务策略与分散决策下的服务策略、相反优先权服务策略以及动态协同下的服务策略进行对比,说明了最优服务能力分配策略的优越性和有效性。     

设备多状态、多类顾客制造系统的生产速率和库存分配联合决策

在生产制造系统中, 设备状态严重制约系统产能, 并增加生产过程的不确定性. 为应对不确定性对系统的影响, 对顾客进行细分, 实施差异化服务. 在顾客泊松达到、 缺货不补的假设下, 研究了设备多状态、多类顾客制造系统的生产和库存分配联合决策问题. 利用马尔科夫决策理论, 建立了系统在无限期期望折扣总成本准则和平均成本准则下的最优方程, 并证明了最优策略具有相似的结构性质. 最优生产速率策略是生产阈值水平随设备状态非增的阈值策略, 即当库存水平降至该阈值水平之下时, 以允许的最大生产速率生产, 否则不生产. 最优库存分配策略是分配阈值水平随设备状态非增的阈值策略. 另外, 缺货成本大的顾客具有较低的分配阈值.     

考虑积欠订货的MTS系统的生产与库存配给

考虑一个供应商以面向库存生产的方式制造某个产品出售给多个客户.客户以批量进行订货,其到达供应商处的需求若未能即时满足则视为积欠订货.供应商根据每个客户的积欠订货成本将其划分为若干个需求类.文中根据客户每次订货是否可分批交货,分别提出了当客户订货可分割和不可分割时供应商的最优生产和库存配给策略.分析表明客户订货是否可分割对于供应商的生产控制策略没有影响,但会影响到库存配给策略.另外,供应商的最优生产控制策略可用一个取决于系统状态的基准库存水平表示,最优的库存配给策略则用一个多层的取决于状态的配给水平向量表示.数据分析验证了文中最优策略的有效性,同时表明当客户订货不可分割时,相对于高优先权需求,低优先权需求类订货量的增加会引起供应商成本较大幅度的增加.     

有限时域下多需求类型产品的库存策略

考虑有限时域下面对确定和随机两种需求类型的产品库存系统,使用动态规划法构建该系统的动态模型以求得利润最大化下的最优订货和分配策略.由于动态规划法计算时间过长且在时域滚动环境下未必最优,因此在分析了最优策略性质的基础上设计了一种启发式算法以解决动态规划法的缺陷.数值分析表明启发式算法在绝大多数情况下优于动态规划法.     

有故障制造系统的服务率和预防维护率的最优控制

考虑一类容许预防维护的制造系统的最优控制 .系统同时存在随机故障和修复、随机加工时间、随机预防维护、随机需求等多种不确定因素 .我们运用马尔可夫最优决策过程归纳方法 ,导出机器服务率和预防维护率的最优控制策略 .通过研究最优值函数的凸性、单调性和渐近性 ,证明了最优策略具有简单的阈值结构且被几个阈值参数完全刻画 .即产品库存水平小于相应的阈值时 ,最优决策是选择最大服务率或维护率 ;否则 ,停止生产或维护 .进而讨论了这些阈值之间的关系 .数值例子说明了本文的结论 .     

考虑库存能力约束的批量问题与定价的联合决策

针对多周期离散时间情形,研究了库存能力约束下如何有效地协调定价决策与批量决策,使得企业利润最大化。建立了非线性混合整数规划模型。分析了最优解的特征,详细讨论了子问题的求解方法。提出了基于动态规划的精确算法,可以在多项式时间内求解出联合决策问题的最优定价与最优生产计划。实验结果分析了库存能力与最优利润、最优生产计划之间的关系。     

带有时变短缺量拖后率且需求依赖库存水平的EOQ模型

基于需求线性依赖于库存水平的变质性物品的EOQ模型,通过考虑随时间变化的短缺量拖后率对库存订货策略的影响,建立了一类具有一般形式的短缺部分拖后的库存补充模型.经过分析得到了此类库存模型最优解存在的必要条件,并针对随缺货时间变化的短缺拖后率函数具体研究了模型最优解的存在性与惟一性.最后,给出了数值算例说明了模型在实际中的应用.     

需求季节性变动的血液库存系统仿真研究

以国内某大型医院的血液库存系统为对象,建立了一个离散事件系统仿真模型,根据该血液库存系统运行的历史数据统计得到模型中参数的分布规律,通过仿真模型的重复运行得出了系统的最优订货点.考虑到该系统需求季节性变动的特征,对模型进行了改进,提出了一个预期订货点模型,仿真实验表明预期订货点策略能更有效地降低库存成本.本文的研究有助于血液库存管理措施的制定与改进,对其它易变质物品库存管理也有一定的借鉴作用.     

基于固定分割的库存路径问题最优策略

针对由单个供应商和多个零售商组成的两级供应链分配系统,研究了一体化的库存路径问题.为了节省整个供应链的费用,重新设计了对零售商的区域分割算法.在此基础上,确定了出零售商订货周期与供应商订货周期的大小关系,通过引入周期比例向量,设计了一个全新的整数倍时间策略,给出了详细的理论分析,证明该策略是最优的整数倍时间策略.数字实验结果表明,该策略比其他策略具有明显优越性.     

库存成本预算约束下大规模定制生产系统的零部件库存策略

从资源有效分配的角度研究了大规模定制生产系统中各零部件的最优订货点,分析了零部件的库存持有成本与零部件加工时间,以及产品定制环节生产时间等因素对零部件的最优订货点和大规模定制生产系统收益的影响。通过数值分析,发现任何一种零部件库存持有成本的增加将导致所有零部件订货点的下降,并导致整个系统的期望收益的下降;零部件加工时间的增加将导致该零部件订货点的上升,导致其他零部件订货点的下降,并导致整个系统的期望收益的下降。     

Optimal production lot size with process deterioration under an extended inspection policy

A mathematical model to determine the optimal production lot size for a deteriorating production system under an extended product inspection policy is developed. The last-K product inspection policy is considered so that the nonconforming items can be reduced, under which the last K products in a production lot are inspected and the nonconforming items from those inspected are reworked. Consider that the products produced towards the end of a production lot are more likely to be nonconforming, is proposed an extended product inspection policy for a deteriorating production system. That is, in a production lot, product inspections are performed among the middle K1 items and after inspections, all of the last K2 products are directly reworked without inspections. Our objective here is the joint optimization of the production lot size and the corresponding extended inspection policy such that the expected total cost per unit time is minimized. Since there is no closed form expression for our optimal policy, the existence for the optimal production inspection policy and an upper bound for the optimal lot size are obtained. Furthermore, an efficient solution procedure is provided to search for the optimal policy. Finally, numerical examples are given to illustrate the proposed model and indicate that the expected total cost per unit time of our product inspection model is less than that of the last-K inspection policy.     

Performance Analyses of Production Inventory Systems Considering Service Time and Product Returns of Online Shopping

This paper considers a production inventory system with service time and product returns,dependent on the characteristics of online shopping behaviors. The customers arrive according to a Poisson process, in which the arriving customer requires an item in the inventory, as well as a server service that the service time is exponentially distributed. Moreover, there is one production facility to produce items according to(s, S) policy, and the production time also follows an exponential distribution. In the beginning, the stationary joint distribution is obtained in the product form for the queue length and the on-hand inventory level. Additionally, the resulting distribution is applied to derive some performance measures, which can be adopted to numerically calculate the optimal(s, S)policy. Finally, numerical analyses are processed to investigate the effects of some system parameters on the performance measures. The numerical results clearly indicate that the product return rate has a significantly monotonic effect on the optimal policy and optimal cost.     

多设备系统的生产批量、质量控制与预知维护联合优化

针对由多台设备通过串、并混联构成的多阶段生产系统,对其生产批量、质量控制以及预知维护进行了联合建模与优化.系统中的各台设备随时间逐渐发生劣化,可靠性及产品加工质量随之降低.在每个生产批量结束时,对各设备进行状态检测并评估其在下个生产期内的可靠性.预知维护同时以设备的可靠性、结构重要度以及产能比为决策依据,以合理分配维护资源.在每个阶段设置质检台以实时检测各设备加工产品的质量,并根据质量反馈信息,对次品率超过控制阈值的设备进行预防性更换以改善性能提高产品质量.以批量生产周期、质量控制阈值以及预知维护参数为三维联合决策变量,建立了有限时域内的平均费用率模型.基于蒙特卡罗仿真和响应曲面法设计了优化算法,实现了对模型的快速近似求解.最后通过一个实例演示了本模型,并对结果作了相关统计学分析.     

制造企业衍生服务运营模式决策：自营与外包的权衡

随着服务在制造企业创收中占比的不断增加，服务衍生已成为实现服务型制造的有效手段，但产品制造的相对集中与服务提供的绝对分散困扰着制造企业衍生服务的自营/外包决策。针对1家制造企业和1家服务承包商出售一类实物产品及一项衍生服务的情形，构建了衍生服务自营与外包两类模式下的博弈模型。结果表明：衍生服务自营/外包的决策受服务水平、产品服务相关性、服务提供优势系数及收益共享系数等多因素影响；自营或外包模式下，衍生服务水平及服务提供优势系数对双方利润的促进作用存在边界，且产品服务相关性对衍生服务水平以及双方利润存在促进作用；外包模式下，收益共享系数的制定应以实现外包双方价值更大创造为目的。     

服务台"修复非新"的M/G/1排队系统更换模型研究

研究了M/G/1服务台“修复非新”的排队系统的最优更换策略。在假定服务台可修且不能“修复如新”和服务台的寿命服从指数分布的前提下,利用几何过程和更新过程,以被服务的顾客数N为其更换策略,以系统经长期运行单位时间內的期望效益为目标函数,选择最优的更换策略N~*,使得这一目标函数达到最大值。求出了系统经长期运行单位时间內期望效益的明显表达式。最后对结果进行了讨论。     

带学习效应的二级易变质产品供应链的最优策略研究

研究了由一个制造商和一个分销商组成的易变质产品二级供应链的最优生产与订购策略. 有限时期内,上游制造商采取按订单生产的方式应对下游分销商的需求, 制造商生产过程以及分销商订购过程具有学习效应, 对此建立二级供应链系统决策问题的数学模型. 目标是要确定使得系统总成本最低的决策变量, 包括生产量, 订购次数以及订购时间. 通过分析系统的成本结构,利用将订购次数松弛为连续变量的技巧, 证明了系统最优策略的存在性和唯一性, 给出了最优策略的求解方法. 最后通过应用实例进行了验证.     

COORDINATING PRODUCTION AND RECYCLING DECISIONS WITH STOCHASTIC DEMAND AND RETUR

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints ? the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.     

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.