生产服务系统优先权能力协同分配策略

随着传统制造企业的经营模式向服务型制造的转变,企业所面对的传统生产库存系统转变为生产服务系统. 研究了由生产设施和服务中心组成的柔性生产服务系统的生产和服务能力协同分配问题. 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服务. 管理者在生产和服务能力均有限的情况下需要决定将生产(服务)能力分配给哪一类产品(服务订单). 在集中决策下通过边际分析得到了最优服务能力分配策略.通过数值实验得到了最优生产策略的特征,然后基于最优策略特征,设计了固定优先权基本库存策略作为生产能力分配策略. 最后通过数值实验分析了由最优服务策略和设计的生产策略构成的协同能力分配策略的有效性,为企业的运作管理提供理论指导.     

地面站系统服务能力评估指标及其计算方法

针对地面站系统服务能力评估问题,研究了其评估指标及其计算方法.首先从卫星、地面站两个方面建立了地面站系统服务能力评估指标,并就各个指标以及指标的应用进行了分析.然后给出了两种指标计算方法:FCFS(First Come First Service)方法和启发式方法.最后通过实例仿真,表明该指标及方法能够较好的解决地面站系统服务能力评估问题中的是否增建新地面站、是否在某地面站中增加天线等重大决策问题.     

可增加号源策略下高需求门诊的能力配置问题

可增加号源策略,即在额定能力全部约满的情况下,医生可增加额外能力提供给仍有需求的患者.本文以面向预约患者和现场患者的高需求门诊为研究对象,考虑患者爽约不确定性对由额外能力产生的医生超负荷工作量的影响.联合决策额外挂号数量(简称加号数)和分配给预约患者的额定挂号数量,以使净收益期望最大.在理论上推导出额外挂号数量的阈值表达式,并证明当超过相应阈值后,净收益期望是额外挂号数量的单峰函数,其最优解可在有限解空间内决策.基于模型性质设计了求解全局联合最优解的双层枚举算法.实验结果表明,算法具有求解高效性;额外挂号数量(加号数)随爽约概率的增大而增加,受额定挂号数量的影响不大;加号策略有效增强了分配给预约患者的额定挂号数量面对爽约概率变化下的稳定性.     

透明转发器卫星通信系统在干扰条件下的容量

提出了存在上行干扰时透明转发器卫星通信系统的容量分析算法。以DS(directsequence)扩频系统为例,分析了透明转发器卫星通信系统存在上行干扰时的链路性能,进行了理论推导,给出了系统在具体干扰条件下容量分析的闭合表达式,从而实现了透明转发器卫星通信系统在干扰条件下的容量计算。研究结果表明:通过采取一定的抗干扰策略,在强干扰条件下透明转发器进入限幅状态之后,系统仍然具有一定容量。     

Knowledge-based decision support system for tool management in flexible manufacturing system

Tool management is not a single, simple activity, it is comprised of a complex set of functions, especially in a flexible manufacturing system (FMS) environment. The issues associated with tool management include tool requirement planning, tool real-time scheduling, tool crib management, tool inventory control, tool fault diagnosis, tool tracking and tool monitoring. In order to make tools flow into/out of FMS efficiently, this work is aimed to design a knowledge-based decision support system (KBDSS) for tool management in FMS. Firstly an overview of tool management functions is described. Then the structure of KBDSS for tool management and the essential agents in the design of KBDSS are presented. Finally the individual agents of KBDSS are discussed for design and development.     

弹性高超声速飞行器智能控制系统设计

针对气动舵受限下的弹性高超声速飞行器控制问题, 提出一种基于神经自适应的智能控制方案。在速度子系统的设计过程中, 为了降低对模型参数的依赖程度, 应用强化学习算法在线调整比例积分微分(proportional integral derivative, PID)控制参数, 给出智能PID控制策略。对于高度子系统, 考虑气动舵的动态特性, 利用神经自适应方法对模型未知函数及不确定项进行逼近。为了处理气动舵的约束问题, 以非线性模型预测控制为优化分配模板生成大量样本数据集, 经离线训练得到深度神经网络代替求解复杂优化问题和控制分配的过程。此外, 通过引入自适应超螺旋微分器处理外部扰动, 增强了系统的鲁棒性。利用Lyapunov方法证明了所设计控制器的稳定性, 并通过仿真验证了所设计控制方案能够快速计算控制指令, 实现高精度跟踪控制。     

Optimal design for a retrial queueing system with state-dependent service rate

This paper considers a single server retrial queue in which a state-dependent service policy is adopted to control the service rate. Customers arrive in the system according to a Poisson process and the service times and inter-retrial times are all exponentially distributed. If the number of customers in orbit is equal to or less than a certain threshold, the service rate is set in a low value and it also can be switched to a high value once this number exceeds the threshold. The stationary distribution and two performance measures are obtained through the partial generating functions. It is shown that this state-dependent service policy degenerates into a classic retrial queueing system without control policy under some conditions. In order to achieve the social optimal strategies, a new reward-cost function is established and the global numerical solutions, obtained by Canonical Particle Swarm Optimization algorithm, demonstrate that the managers can get more benefits if applying this state-dependent service policy compared with the classic model.     

考虑撤单率的电商配送服务能力自建与外包博弈模型与求解

针对在线冷静期内产生消费者撤单行为情况下电商配送服务能力的自建与外包决策问题,引入撤单率,从是否进行合作的角度给出了完全合作博弈、完全非合作博弈和不完全非合作三种合作强度的动态博弈模型,并将其中两种情形划分为三阶段动态博弈过程,采用逆向递归法求解这两种情形下各子博弈均衡解,得到了在线购买环境下电商配送服务能力自建与外包的最优解集.进一步地,在第三种情形下设计了成本分担、利润分配以及风险规避三种子博弈模型,以增强模型的灵活性.数值算例与分析表明电商配送服务能力博弈中,电商决策者能够有效实现撤单行为与成本变动影响下动态博弈的帕累托优化.     

A comparative study of the inventory system with service facility and postponed demands

In this article, we present a continuous review （s,S） inventory system with a service facility consisting of finite buffer （capacity N ） and a single server. The customers arrive according to a Poisson process. The individual customer＇s unit demand is satisfied after a random time of service, which is assumed to be exponential. When the inventory level drops to s＇an order for Q（= S-s） items is placed. The lead time of reorder is assumed to be exponential distribution. An arriving customer, who finds the buffer is full, enters into the pool of infinite size or leaves the system according to a Bernolli trial. At the time of service completion, if the buffer size drops to a preassigned level L （1 〈 L 〈 N） or below and the inventory level is above s, we select the customers from the pool according to two different policy ： in first policy, with probability p （0 〈 p 〈 1） we select the customer from the head of the pool and we place the customer at the end of the buffer; in the second policy, with p （0 〈 p 〈 1） the customer from the pool is transferred to the buffer for immediate service and after completion of his service we provide service to the customer who is in the buffer with probability one. If at a service completion epoch the buffer turns out to be empty, there is at least one customer in the pool and the inventory level is positive, then the one ahead of all waiting in the pool gets transferred to the buffer, and his service starts immediately. The joint probability distribution of the number of customers in the pool, number of customers in the buffer and the inventory level is obtained in the steady-state case. Various stationary system performance measures are computed and total expected cost rate is calculated. A comparative result of two models is illustrate numerically.     

分布式卫星SAR柔性仿真系统设计与实现

构建分布式卫星合成孔径雷达(synthetic aperture radar, SAR)仿真系统对于分布式卫星SAR系统设计、测试与验证、减少系统研制费用、降低决策风险,以及系统的在轨运行管理,都具有重要的意义。围绕分布式卫星SAR仿真系统设计需求,提出了分布式卫星SAR系统柔性仿真框架模型,并讨论了设计和实现过程中的关键技术。该系统的实现和应用验证了框架和技术路线的可行性,为未来进一步完善和广泛应用奠定了基础。