On a two-server finite queuing system with ordered entry and deterministic arrivals

Consider a two-server, ordered entry, queuing system with heterogeneous servers and finite waiting rooms in front of the servers. Service times are negative exponentially distributed. The arrival process is deterministic. A matrix solution for the steady state probabilities of the number of customers in the system is derived. The overflow probability will be used to formulate the stability condition of a closed-loop conveyor system with two work stations.     

Two-phase queuing system with unreliable servers

A two-phase queuing system with a finite number of places in the buffer between the phases and unreliable servers is considered. It is shown that the queuing system can be interpreted as a queue system working in a random environment. An ergodicity condition is found. An asymptotic of the traffic coefficient is obtained for the exponential case.     

Inventory based allocation policies for flexible servers in?serial systems

Motivated by an industry example, we study a two-station serial system in which we allocate flexible servers in order to maximize throughput. We investigate two cases which are different in the way that servers work together when at the same station; namely collaboratively or non-collaboratively. For the collaborative case we prove the optimal policy to be such that the servers work together at a single station at any point in time. In addition to the policy being state-dependent, it also follows a switching-curve structure. In the non-collaborative case, on the other hand, it may be optimal to allocate servers to different stations. Some numerical examples and results regarding policy assignments, switching curves, and system throughput are presented.     

Optimal assignment of servers to tasks when collaboration is inefficient

Consider a Markovian system of two stations in tandem with finite intermediate buffer and two servers. The servers are heterogeneous, flexible, and more efficient when they work on their own than when they collaborate. We determine how the servers should be assigned dynamically to the stations with the goal of maximizing the system throughput. We show that the optimal policy depends on whether or not one server is dominant (i.e., faster at both stations) and on the magnitude of the efficiency loss of collaborating servers. In particular, if one server is dominant then he must divide his time between the two stations, and we identify the threshold policy the dominant server should use; otherwise each server should focus on the station where he is the faster server. In all cases, servers only collaborate to avoid idleness when the first station is blocked or the second station is starved, and we determine when collaboration is preferable to idleness as a function of the efficiency loss of collaborating servers.     

Stochastic Decomposition in M/M/∞ Queues with Markov Modulated Service Rates

Motivated by the need to study transportation systems in which incidents cause traffic to slow down, we consider an M/M/∞ queueing system subject to random interruptions of exponentially distributed durations. System breakdowns, where none of the servers work, as well as partial failures, where all servers work with lower efficiency, are investigated. In both cases, it is shown that the number of customers present in the system in equilibrium is the sum of two independent random variables. One of these is the number of customers present in an ordinary M/M/∞ queue without interruptions.     

Simulation of a random fuzzy queuing system with multiple servers

The paper considers a queuing system that has k servers and its interarrival times and service times are random fuzzy variables.We obtain a theorem concerning the average chance of the event “r servers (r ≤ k) are busy at time t”, provided that all the servers work independently. We simulate the average chance using fuzzy simulation method and obtain some results on the number of servers that are busy. Some examples to illustrate the simulation procedure are also presented.     

Modeling traffic flow interrupted by incidents

A steady-state M/M/c queueing system under batch service interruptions is introduced to model the traffic flow on a roadway link subject to incidents. When a traffic incident happens, either all lanes or part of a lane is closed to the traffic. As such, we model these interruptions either as complete service disruptions where none of the servers work or partial failures where servers work at a reduced service rate. We analyze this system in steady-state and present a scheme to obtain the stationary number of vehicles on a link. For those links with large c values, the closed-form solution of M/M/∞ queues under batch service interruptions can be used as an approximation. We present simulation results that show the validity of the queueing models in the computation of average travel times.     

Synchronous working vacation policy for finite-buffer multiserver queueing system

This paper presents modeling and analysis of unreliable Markovian multiserver finite-buffer queue with discouragement and synchronous working vacation policy. According to this policy, c servers keep serving the customers until the number of idle servers reaches the threshold level d; then d idle servers take vacation altogether. Out of these d vacationing servers, d_W servers may opt for working vacation i.e. they serve the secondary customers with different rates during the vacation period. On the other hand, the remaining d − d_W = d_V servers continue to be on vacation. During the vacation of d servers, the other e = c − d servers must be present in the system even if they are idle. On returning from vacation, if the queue size does not exceed e, then these d servers take another vacation together; otherwise start serving the customers. The servers may undergo breakdown simultaneously both in regular busy period and working vacation period due to the failure of a main control unit. This main unit is then repaired by the repairman in at most two phases. We obtain the stationary performance measures such as expected queue length, average balking and reneging rate, throughput, etc. The steady state and transient behaviours of the arriving customers and the servers are examined by using matrix analytical method and numerical approach based on Runge-Kutta method of fourth order, respectively. The sensitivity analysis is facilitated for the transient model to demonstrate the validity of the analytical results and to examine the effect of different parameters on various performance indices.     

Partial Pooling in Tandem Lines with Cooperation and Blocking

For a tandem line of finite, single-server queues operating under the production blocking mechanism, we study the effects of pooling several adjacent stations and the associated servers into a single station with a single team of servers. We assume that the servers are cross-trained (so that they can work at several different stations) and that two or more servers can cooperate on the same job. For such a system, we provide sufficient conditions on the service times and sizes of the input and output buffers at the pooled station under which pooling will decrease the departure time of each job from the system (and hence increase the system throughput). We also show that pooling decreases the total number of jobs in the system at any given time and the sojourn time of each job in the system if the departure time of each job from the system is decreased by pooling and there is an arrival stream at the first station. Moreover, we provide sufficient conditions under which pooling will improve the holding cost of each job in the system incurred before any given time, and extend our results to closed tandem lines and to queueing networks with either a more general blocking mechanism or probabilistic routing. Finally, we present a numerical study aimed at quantifying the improvements in system performance obtained through pooling and at understanding which stations should be pooled to achieve the maximum benefit. Our results suggest that the improvements gained by pooling may be substantial and that the bottleneck station should be among the pooled stations in order to obtain the greatest benefit. AMS subject classification: 90B22     

A stochastic recirculation system with random access

A model for a stochastic recirculation system with randomly accessed multiple heterogeneous servers, no waiting rooms, and exponentially-distributed service times is provided. In this system the units are assigned to one of the servers upon arrival by random mechanism. Units which find all servers busy recirculate and combine with the incoming arrivals and join those already in the system to initiate the next cycle. The equilibrium behavior of the internal and external stochastic processes of the system is analyzed using a two parameter approximation. A simulation model is also developed and its behavior is compared against the analytical model at the steady state. The model with randomly-accessed servers is compared to a single server model already established in the literature. The performance of the model is then examined for a wide range of parameter values to obtain conclusions about its optimal performances.     

Static and dynamic server allocation in systems with on/off sources

A system consisting of a number of servers, where demands of different types arrive in bursts (modelled by interrupted Poisson processes), is examined in the steady state. The problem is to decide how many servers to allocate to each job type, so as to minimize a cost function expressed in terms of average queue sizes. First, an exact analysis is provided for an isolated IPP/M/n queue. The results are used to compute the optimal static server allocation policy. The latter is then compared to four heuristic policies which employ dynamic switching of servers from one queue to another (such switches take time and hence incur costs). This work was carried out in the framework of the collaborative project DOPCHE (Dynamic Operative Policies for Commercial Hosting Environments), funded by the UK Engineering and Physical Sciences Research Council under its E-Science programme. The support of the Network of Excellence EuroNGI, funded by the EU, is also acknowledged.     

PH/M/c可修排队系统

研究了一个修理工和c个服务台的可修排队系统.假设顾客的到达过程为PH更新过程,服务台在忙时与闲时具有不同的故障率.顾客的服务时间、服务台的寿命以及服务台的修理时间均服从指数分布.通过建立系统的拟生灭过程,得到了系统稳态分布存在的充要条件.利用矩阵几何解方法,给出了系统的稳态队长.在此基础上,得到了系统的某些排队论和可靠性指标.     

A scheduling problem for several parallel servers

In this paper, we study a scheduling problem of jobs from two different queues on several parallel servers. Jobs have exponentially distributed processing times, and incur costs per unit of time, until they leave the system, and there are no arrivals to the system at any time. The objective is to find the optimal strategy, i.e., to allocate the servers to the queues, such that the expected holding costs are minimized. We give a sufficient condition for which it is always optimal to allocate the servers only to jobs of a certain queue. Finally, the case of two servers is completely solved.     

A Push–Pull Network with Infinite Supply of Work

We consider a two-node multiclass queueing network with two types of jobs moving through two servers in opposite directions, and there is infinite supply of work of both types. We assume exponential processing times and preemptive resume service. We identify a family of policies which keep both servers busy at all times and keep the queues between the servers positive recurrent. We analyze two specific policies in detail, obtaining steady state distributions. We perform extensive calculations of expected queue lengths under these policies. We compare this network with the Kumar–Seidman–Rybko–Stolyar network, in which there are two random streams of arriving jobs rather than infinite supply of work.     

Heavy traffic resource pooling in parallel‐server systems

We consider a queueing system with r non‐identical servers working in parallel, exogenous arrivals into m different job classes, and linear holding costs for each class. Each arrival requires a single service, which may be provided by any of several different servers in our general formulation; the service time distribution depends on both the job class being processed and the server selected. The system manager seeks to minimize holding costs by dynamically scheduling waiting jobs onto available servers. A linear program involving only first‐moment data (average arrival rates and mean service times) is used to define heavy traffic for a system of this form, and also to articulate a condition of overlapping server capabilities which leads to resource pooling in the heavy traffic limit. Assuming that the latter condition holds, we rescale time and state space in standard fashion, then identify a Brownian control problem that is the formal heavy traffic limit of our rescaled scheduling problem. Because of the assumed overlap in server capabilities, the limiting Brownian control problem is effectively one‐dimensional, and it admits a pathwise optimal solution. That is, in the limiting Brownian control problem the multiple servers of our original model merge to form a single pool of service capacity, and there exists a dynamic control policy which minimizes cumulative cost incurred up to any time t with probability one. Interpreted in our original problem context, the Brownian solution suggests the following: virtually all backlogged work should be held in one particular job class, and all servers can and should be productively employed except when the total backlog is small. It is conjectured that such ideal system behavior can be approached using a family of relatively simple scheduling policies related to the cμ rule. This revised version was published online in June 2006 with corrections to the Cover Date.     

Convexity properties of the overflow in an ordered-entry system with heterogeneous servers

The overflow probability in an Erlang loss system is known to be decreasing convex in the number of servers. Here we consider the GI/M/m loss system with ordered entry and heterogeneous servers. We show that adding a sequence of servers with non-increasing (non-decreasing) service rates will yield a decreasing convex (log-concave) sequence of overflow probabilities. An optimal server allocation problem is solved as a direct application of these results.     

Emergency path restoration problems

We consider the problem of optimally scheduling the restoration of edges of a transportation network destroyed/damaged by a disaster. The restoration is performed by service units (servers) which have fixed restoration speeds. If several servers work simultaneously at the same point of the network, their collective restoration speed is the sum of their individual restoration speeds. The servers are initially located at some nodes. Each server can travel within the already restored part of the network with infinite speed, that is, at any time can immediately relocate to another point of the same connected component of the already restored part of the network. It is required to minimize a scheduling objective that can be expressed as the maximum or the sum of nondecreasing functions of the recovery times of the nodes, where the recovery time of a node is the time when the node is reached for the first time by a server. We present polynomial-time algorithms on path networks for problems with fixed initial locations of the servers. For problems with flexible locations that should also be optimized, we present polynomial-time algorithms for the case of equal restoration speeds of the servers, and prove that the problems are strongly NP-hard if the restoration speeds of the servers can be different.     

Maximizing throughput in finite-source parallel queue systems

Motivated by the dispatching of trucks to shovels in surface mines, we study optimal routing in a Markovian finite-source, multi-server queueing system with heterogeneous servers, each with a separate queue. We formulate the problem of routing customers to servers to maximize the system throughput as a Markov Decision Process. When the servers are homogeneous, we demonstrate that the Shortest Queue policy is optimal, and when the servers are heterogeneous, we partially characterize the optimal policy and present a near-optimal and simple-to-implement policy. We use the model to illustrate the substantial benefits of pooling, by comparing it to the permanent assignment of customers to servers.     

带有负顾客的M/M/c多重工作休假排队

考虑服务台在休假期间不是完全停止工作,而是以相对于正常服务期低些的服务率服务顾客的M/M/c工作休假排队模型.在此模型基础上,针对现实的M/M/c排队模型中可能出现的外来干扰因素,提出了带有负顾客的M/M/c工作休假排队这一新的模型.服务规则为先到先服务.工作休假策略为空竭服务异步多重工作休假.抵消原则为负顾客一对一抵消处于正常服务期的正顾客,若系统中无处于正常服务期的正顾客时,到达的负顾客自动消失,负顾客不接受服务.首先,由该多重休假模型得到其拟生灭过程及生成元矩阵,然后运用矩阵几何方法给出系统队长的稳态分布表达式和若干系统指标.     

Workforce cross-training decisions in field service systems with two job types

When job types are heterogeneous in a multi-server service system, pooling servers to reduce system delay requires cross-training. Managers should balance a reduction in customer waiting time with high service costs and possibly reduced server efficiency due to cross-training. In a field service system with two job types and a fixed number of servers, the determination of the mix of dedicated and cross-trained servers is a critical managerial decision. We were motivated by a real field service situation to study a model where the objective is to minimize the sum of the average service costs and the customer delay costs per unit time. We use simulation to investigate the impact of various system parameters such as the number of servers, server utilization, and server efficiency on the optimal workforce mix.