一类排队服务系统的最优控制策略研究

建立一个双阈值排队服务模型, 用来协调顾客的等待时间和服务系统的运行成本. 采用一种精细的概率分解方法获得瞬态和稳态队长的概率分布性质; 再根据系统稳态性能指标, 建立系统营运利润函数, 并设计一种针对双离散变量函数的全局优化收索算法来研究最优控制策略; 进一步的数值实验揭示出双重阈值策略的优越性.     

Assessing an ambulance service with queuing theory

We describe an ambulance service in terms of its main operation parameters and strategic decision variables. Assisted by queuing theory, we calculate the key performance indicators (KPI) that concern the manager and the KPI that concern the patient. We use them to improve the operation of a private ambulance service in Chile. First, we evaluate whether the historical performance is consistent with the resources deployed. Then, we estimate the impact of some operational enhancements, such as reducing the cycle time or enlarging the fleet. Finally, we optimize the geographical coverage of the bases. We conclude that simple mathematical expressions are very useful to evaluate and improve the operation.     

基于排队论模型的网络拥塞率研究

分析了目前拥塞控制存在的问题,以排队论模型为基础对网络拥塞率进行了研究,从一个路由器的角度出发研究网络拥塞问题,提出了基本模型,给出了求解瞬时拥塞率的算法,并得到了稳态拥塞率的解析表达式.通过数值结果指出,路由器缓存的适当增加可以降低拥塞率,但过渡增加反而会增加拥塞率;增加路由器的CPU处理速度可以降低拥塞率.     

基于马氏决策过程的概率离散事件系统最优控制

使用马氏决策过程研究了概率离散事件系统的最优控制问题.首先,通过引入费用函数、目标函数以及最优函数的定义,建立了可以确定最优监控器的最优方程.之后,又通过此最优方程获得了给定语言的极大可控、∈-包含闭语言.最后给出了获得最优费用与最优监控器的算法.     

Validation of a computer performance model of the exponential queuing network family

Summary The applicability and accuracy of a general queuing network approach to the modeling of computer performance was tested in an actual production environment. The validation exercise established that such an approach had both sufficient flexibility and precision to be of use in long range planning efforts. The accuracy of the results further suggests that these techniques may be successfully extended to a wide range of uses.     

Flow control using the theory of zero sum Markov games

Considers the problem of dynamic flow control of arriving packets into an infinite buffer. The service rate may depend on the state of the system, may change in time, and is unknown to the controller. The goal of the controller is to design an efficient policy which guarantees the best performance under the worst service conditions. The cost is composed of a holding cost, a cost of rejecting customers (packets), and a cost that depends on the quality of the service. The problem is studied in the framework of zero-sum Markov games, and a value iteration algorithm is used to solve it. It is shown that there exists an optimal stationary policy (such that the decisions depend only on the actual number of customers in the queue); it is of a threshold type, and it uses randomization in at most one state     

Dynamic control of service rates in queuing networks

A method for dynamic control of service rates in closed exponential queuing networks is proposed. The performance of queuing networks with the service-rate control is analyzed, and the main steady-state network characteristics are computed using an analytic approximation. A simple example of a queuing network with controlled service rates is considered as an illustration. The efficiency of the service-rate control is confirmed by Monte Carlo simulations, which, as a by-product, also show acceptable accuracy of our analytical approximations.     

Optimal pricing decision of composite service offered by network providers in E-commerce environment

Electronic Commerce Research - With the increasing demand of consumers for diversified network services, more and more network service providers are competing fiercely in providing network...     

Optimal control of water distribution systems by network flow theory

This paper presents a modeling technique and an optimal control scheme for water distribution networks. To overcome the large scale and nonlinearity of the network, a network aggregation method and a two-level control scheme are developed. The first level of the scheme decides operating points using a nonlinear optimization method, where the pressure/flow equations are solved using a high-speed technique derived from network flow theory. The second level is a feedback control around the operating points, which absorbs estimate error and small variations in consumption. The scheme has been implemented on a minicomputer system and is presently in operation.     

Admission control of hospitalization with patient gender by using Markov decision process

Admission control of hospitalization considering patient gender is an interesting issue in the study of hospital bed management. This paper addresses the decision on the admission of patients who should immediately be admitted into a same-gender room or rejected. Note that a patient is admitted depending on different conditions, such as his/her health condition, gender, the availability of beds, the length of stay, and the reward of hospitalization. Focusing on the key factor, patient gender, this paper sets up an infinite-horizon total discounted reward Markov decision process model with the purpose to maximize the total expected reward for the hospital, which leads to an optimal dynamic policy. Then, the structural properties of the optimal policy are analyzed. Additionally, a value iteration algorithm is proposed to find the optimal policy. Finally, some numerical experiments are used to discuss how the optimal dynamic policy depends on some key parameters of the system. Furthermore, the performance of the optimal policy is discussed though comparison with the three other policies by means of simulating different scenarios.     

Optimal scheduling in queuing network models of high-volume commercial web sites

The optimal control of various performance-based measures in high-volume commercial web sites requires a fundamental understanding of the interactions between the diverse set of Internet services that support customer needs and the different importance levels of these services to both the customer and the e-commerce merchant. We present here a study of the control policy for each server in a multiclass queuing network that maximizes a particular function of profit, or minimizes a particular function of cost, across the different classes of Internet services.     

Optimal control of noisy finite-state Markov processes

This paper treats the problem of optimal control of finite-state Markov processes observed in noise. Two types of noisy observations are considered: additive white Gaussian noise and jump-type observations. Sufficient conditions for the optimality of a control law are obtained similar to the stochastic Hamilton-Jacobi equation for perfectly observed Markov processes. An illustrative example concludes the paper.     

多代理系统下的主动配电网故障恢复博弈策略

在保障主动配电网可靠恢复前提下,为实现供电侧与用户侧利益均衡,本文提出了多代理系统(multiagent system,MAS)下的主动配电网故障恢复博弈策略.为充分考虑电网和电力用户对故障恢复的决策影响,设计了由电网代理、用户总代理和协调代理构成的MAS,建立了MAS信息传输模型.然后,构建了供电侧和用户侧在故障恢复中的利益函数、恢复策略空间,以及以电网代理和用户总代理作为参与人的合作博弈恢复模型.电网代理和用户总代理分别以改进的蚁群算法和统计方法进行分布并行计算,协调代理以双方共同的利益函数作为寻优目标通过迭代算法求得满足纳什均衡的恢复策略.本文以IEEE69节点模型为例,分别对单故障和连锁故障恢复情景求解,验证了本文所提策略的有效性.     

An application of Markov potential theory to Markovian decision processes

The aim of this paper is to identify the denumerable stochastic systems which have an optimal strategy, namely, to give general sufficient conditions of the existence of an optimal strategy for denumerable Markovian decision processes. The aim is accomplished by using Markov potential theory and showing the range of the validity of a method to find an optimal strategy called Howard's technique. Since Markov potential theory helps to characterize the properties of evaluations of strategies on such processes, it plays an important role to find the sufficient conditions mentioned above

For Markov potential theory, new concepts are introduced such as absorbable chains, quasi-potentials, etc., and using them, sufficient conditions for the existence of a solution of the equation x = f+Px are generalized to the one's for cyclic chains and multi-chains

The results obtained in this paper are as follows : if a system represents a strong Markov chain for any strategy, then there exists an optimal strategy with respect to the total or the mean expected earnings, and for any stochastic system there exists an optimal strategy with respect to the discounted total expected earnings.     

Specification and simulation of queuing network models using Domain-Specific Languages

Queuing network models (QNMs) provide powerful notations and tools for modeling and analyzing the performance of many different kinds of systems. Although several powerful tools currently exist for solving QNMs, some of these tools define their own model representations, have been developed in platform-specific ways, and are normally difficult to extend for coping with new system properties, probability distributions or system behaviors. This paper shows how Domain Specific Languages (DSLs), when used in conjunction with Model-driven engineering techniques, provide a high-level and very flexible approach for the specification and analysis of QNMs. We build on top of an existing metamodel for QNMs (PMIF) to define a DSL and its associated tools (editor and simulation engine), able to provide a high-level notation for the specification of different kinds of QNMs, and easy to extend for dealing with other probability distributions or system properties, such as system reliability.     

Optimal fuzzy control of exponential synchronisation via genetic algorithm

In this study, a novel approach via GA-based fuzzy control is proposed to realize the exponential optimal H^∞ synchronisation of MTDC systems. A robustness design of model-based fuzzy control is first presented to overcome the effect of modelling errors between the MTDC systems and T-S fuzzy models. Next, a delay-dependent exponential stability criterion is derived in terms of Lyapunov's direct method to guarantee that the trajectories of the slave system can approach those of the master system. Subsequently, the stability conditions of this criterion are reformulated into LMIs. According to the LMIs, a fuzzy controller is then synthesised to exponentially stabilise the error systems. Moreover, the capability of GA in random search for near-optimal solutions, the lower and upper bounds of the search space based on the feedback gains via LMI approach can be set so that the GA will seek better feedback gains of fuzzy controllers to speed up the synchronisation. Additionally, an IGA was proposed to overcome both the shortcomings of premature convergence of GA and local search. According to the IGA, a fuzzy controller is synthesised not only to realise the exponential synchronisation but also to achieve the optimal H^∞ performance by minimising the disturbance attenuation level.     

基于网络排队模型的Monte Carlo多线程电梯交通流优化设计

采用Monte Carlo方法对串并联结合的复合电梯系统进行了分析,应用多线程技术模拟电梯交通流模型,并给出相应的算法流程.将该算法应用到电梯配置测评中,通过对多个仿真实例的比较,根据配置结构,给出各实例的相应性能指标.结果表明,以本模型为基础建立的电梯配置测评系统可以平衡乘客候梯时间和电梯负载之间的关系,对电梯系统的结构配置给出合理建议,证明了Monte Carlo方法在电梯群控系统测评和优化中的可行性和优越性.     

Optimal control of the two-state Markov process in discrete time

Using the control problem of a two-state Markov process in discrete time as an example, we consider the basic stages concerning the application of theory of conditional Markov processes to synthesize optimal algorithms of the control of stochastic systems. It is assumed that the control changes the statistical properties of the states of a controlled plant. The numerical method for solving the problem and the results of solving particular example are presented. The special features of the solution of this problem compared to the well-known problem in continuous time are discussed.     

An open exponential queuing network with limited waiting spaces and losses: A method of approximate analysis

Open exponential queuing networks are considered where each node in a network represents several exponential servers with a joint waiting space (a buffer) of limited capacity. A customer arriving to a node with fully occupied buffer is lost. An assumption is made that the input flow to each node formed as a mixture of the external Poisson flow and the flows coming from other nodes is a Poisson flow. Under this assumption, a method of computing network parameters is presented which is based on solving iteratively a system of nonlinear equations for the unknown nodal flow rates. A method based on Markov chain techniques is presented to find the approximate value of the average conditional sojourn time in the network for customers which completed their service process in the network and for customers which were lost eventually. It is demonstrated for two types of a network (a complete 5-node graph and a 5-node tandem-type system) that the network parameters obtained by the derived analytic method are close to those obtained by the Monte Carlo simulation method.