Optimality of Randomized Trunk Reservation

1994 ◽  
Vol 8 (4) ◽  
pp. 463-489 ◽  
Author(s):  
Eugene A. Feinberg ◽  
Martin I. Reiman
Keyword(s):  
Optimal Policy ◽  
Queueing System ◽  
Blocking Probability ◽  
Average Reward ◽  
Constrained Problem ◽  
Optimal Policies ◽  
Customer Type ◽  
Time Subject

We consider a controlled queueing system that is a generalization of the M/M/c/W queue. There are m types of customers that arrive according to independent Poisson processes. Service times are exponential and independent and do not depend on the customer type. There is room in the system for a total of N customers; if there are N customers in the system, new arrivals are lost. Type j customers are more profitable than type (j + 1 ) customers, j = 2,…, m —, and type 1 customers are at least as profitable as type 2 customers. The allowed control is to accept or reject customers at arrival. No preemption of customers in service is allowed. The goal is to maximize the average reward per unit of time subject to a constraint that the blocking probability of type 1 customers is no greater than a given level.For an M/M/c/c system without a constraint, Miller [12] proved that an optimal policy has a simple threshold structure. We show that, for the constrained problem described above, an optimal policy has a similar structure, but one of the thresholds might have to be randomized. We also derive an algorithm that constructs an optimal policy and describe other forms of optimal policies.

Bias optimal admission control policies for a multiclass nonstationary queueing system

2002 ◽  
Vol 39 (01) ◽  
pp. 20-37 ◽  
Author(s):  
Mark E. Lewis ◽  
Hayriye Ayhan ◽  
Robert D. Foley
Keyword(s):  
Optimal Policy ◽  
Queueing System ◽  
Sufficient Conditions ◽  
System Capacity ◽  
Average Reward ◽  
Finite Capacity ◽  
Long Run ◽  
Optimal Policies ◽  
Service Rates ◽  
Long Run Average Reward

We consider a finite-capacity queueing system where arriving customers offer rewards which are paid upon acceptance into the system. The gatekeeper, whose objective is to ‘maximize’ rewards, decides if the reward offered is sufficient to accept or reject the arriving customer. Suppose the arrival rates, service rates, and system capacity are changing over time in a known manner. We show that all bias optimal (a refinement of long-run average reward optimal) policies are of threshold form. Furthermore, we give sufficient conditions for the bias optimal policy to be monotonic in time. We show, via a counterexample, that if these conditions are violated, the optimal policy may not be monotonic in time or of threshold form.

scholarly journals Optimality of randomized trunk reservation for a problem with a single constraint

2006 ◽  
Vol 38 (01) ◽  
pp. 199-220 ◽  
Author(s):  
X. Fan-Orzechowski ◽  
E. A. Feinberg
Keyword(s):  
Optimal Policy ◽  
Blocking Probability ◽  
Finite Capacity ◽  
Single Constraint ◽  
Customer Type ◽  
Trunk Reservation ◽  
Lagrangian Optimization ◽  
Finite Capacity Queue ◽  
Average Rewards ◽  
Time Subject

We study an optimal admission of arriving customers to a Markovian finite-capacity queue, e.g. an M/M/c/Nqueue, with several customer types. The system managers are paid for serving customers and penalized for rejecting them. The rewards and penalties depend on customer type. The goal is to maximize the average rewards per unit time subject to the constraint on the average penalties per unit time. We provide a solution to this problem based on Lagrangian optimization. For a feasible problem, we show the existence of a randomized trunk reservation optimal policy with the acceptance thresholds for different customer types ordered according to a linear combination of the service rewards and rejection costs. In addition, we prove that any 1-randomized stationary optimal policy has this structure. In particular, we establish the structure of an optimal policy that maximizes the average rewards per unit time subject to the constraint on the blocking probability of either one of the customer types or a group of customer types pooled together.

scholarly journals Optimality of randomized trunk reservation for a problem with a single constraint

2006 ◽  
Vol 38 (1) ◽  
pp. 199-220 ◽  
Author(s):  
X. Fan-Orzechowski ◽  
E. A. Feinberg
Keyword(s):  
Optimal Policy ◽  
Blocking Probability ◽  
Finite Capacity ◽  
Single Constraint ◽  
Customer Type ◽  
Trunk Reservation ◽  
Lagrangian Optimization ◽  
Finite Capacity Queue ◽  
Average Rewards ◽  
Time Subject

We study an optimal admission of arriving customers to a Markovian finite-capacity queue, e.g. an M/M/c/N queue, with several customer types. The system managers are paid for serving customers and penalized for rejecting them. The rewards and penalties depend on customer type. The goal is to maximize the average rewards per unit time subject to the constraint on the average penalties per unit time. We provide a solution to this problem based on Lagrangian optimization. For a feasible problem, we show the existence of a randomized trunk reservation optimal policy with the acceptance thresholds for different customer types ordered according to a linear combination of the service rewards and rejection costs. In addition, we prove that any 1-randomized stationary optimal policy has this structure. In particular, we establish the structure of an optimal policy that maximizes the average rewards per unit time subject to the constraint on the blocking probability of either one of the customer types or a group of customer types pooled together.

Bias optimal admission control policies for a multiclass nonstationary queueing system

2002 ◽  
Vol 39 (1) ◽  
pp. 20-37 ◽  
Author(s):  
Mark E. Lewis ◽  
Hayriye Ayhan ◽  
Robert D. Foley
Keyword(s):  
Optimal Policy ◽  
Queueing System ◽  
Sufficient Conditions ◽  
System Capacity ◽  
Average Reward ◽  
Finite Capacity ◽  
Long Run ◽  
Optimal Policies ◽  
Service Rates ◽  
Long Run Average Reward

We consider a finite-capacity queueing system where arriving customers offer rewards which are paid upon acceptance into the system. The gatekeeper, whose objective is to ‘maximize’ rewards, decides if the reward offered is sufficient to accept or reject the arriving customer. Suppose the arrival rates, service rates, and system capacity are changing over time in a known manner. We show that all bias optimal (a refinement of long-run average reward optimal) policies are of threshold form. Furthermore, we give sufficient conditions for the bias optimal policy to be monotonic in time. We show, via a counterexample, that if these conditions are violated, the optimal policy may not be monotonic in time or of threshold form.

scholarly journals Analysis of Multiserver Queueing System with Opportunistic Occupation and Reservation of Servers

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Bin Sun ◽  
Moon Ho Lee ◽  
Sergey A. Dudin ◽  
Alexander N. Dudin
Keyword(s):  
System Performance ◽  
Queueing System ◽  
Optimal Choice ◽  
Preemptive Priority ◽  
Rate Dependent ◽  
Service Type ◽  
The Subject ◽  
Multiserver Queueing System

We consider a multiserver queueing system with two input flows. Type-1 customers have preemptive priority and are lost during arrival only if all servers are occupied by type-1 customers. If all servers are occupied, but some provide service to type-2 customers, service of type-2 customer is terminated and type-1 customer occupies the server. If the number of busy servers is less than the thresholdMduring type-2 customer arrival epoch, this customer is accepted. Otherwise, it is lost or becomes a retrial customer. It will retry to obtain service. Type-2 customer whose service is terminated is lost or moves to the pool of retrial customers. The service time is exponentially distributed with the rate dependent on the customer’s type. Such queueing system is suitable for modeling cognitive radio. Type-1 customers are interpreted as requests generated by primary users. Type-2 customers are generated by secondary or cognitive users. The problem of optimal choice of the thresholdMis the subject of this paper. Behavior of the system is described by the multidimensional Markov chain. Its generator, ergodicity condition, and stationary distribution are given. The system performance measures are obtained. The numerical results show the effectiveness of considered admission control.

BIAS OPTIMALITY IN A QUEUE WITH ADMISSION CONTROL

1999 ◽  
Vol 13 (3) ◽  
pp. 309-327 ◽  
Author(s):  
Mark E. Lewis ◽  
Hayriye Ayhan ◽  
Robert D. Foley
Keyword(s):  
Admission Control ◽  
Queueing System ◽  
Average Reward ◽  
Objective Functions ◽  
Finite Capacity ◽  
Long Run ◽  
Blackwell Optimality ◽  
Optimal Policies ◽  
Bias Optimality ◽  
Long Run Average Reward

We consider a finite capacity queueing system in which each arriving customer offers a reward. A gatekeeper decides based on the reward offered and the space remaining whether each arriving customer should be accepted or rejected. The gatekeeper only receives the offered reward if the customer is accepted. A traditional objective function is to maximize the gain, that is, the long-run average reward. It is quite possible, however, to have several different gain optimal policies that behave quite differently. Bias and Blackwell optimality are more refined objective functions that can distinguish among multiple stationary, deterministic gain optimal policies. This paper focuses on describing the structure of stationary, deterministic, optimal policies and extending this optimality to distinguish between multiple gain optimal policies. We show that these policies are of trunk reservation form and must occur consecutively. We then prove that we can distinguish among these gain optimal policies using the bias or transient reward and extend to Blackwell optimality.

Optimal control of a flexible server

2004 ◽  
Vol 36 (01) ◽  
pp. 139-170 ◽  
Author(s):  
Hyun-Soo Ahn ◽  
Izak Duenyas ◽  
Rachel Q. Zhang
Keyword(s):  
Optimal Policy ◽  
Dynamic Scheduling ◽  
Sufficient Conditions ◽  
Holding Costs ◽  
Switching Curve ◽  
Necessary And Sufficient ◽  
Dynamic Arrivals ◽  
Flexible Server

We consider the dynamic scheduling of a multiclass queueing system with two servers, one dedicated (server 1) and one flexible (server 2), with no arrivals. Server 1 is dedicated to processing type-1 jobs while server 2 is primarily responsible for processing type-2 jobs but can also aid server 1 with its work. We address when it is optimal for server 2 to aid server 1 with type-1 jobs rather than process type-2 jobs. The objective is to minimize the total holding costs incurred until all jobs in the system are processed and leave the system. We show that the optimal policy can exhibit one of three possible structures: (i) an exhaustive policy for type-2 jobs, (ii) a nonincreasing switching curve in the number of type-1 jobs and (iii) a nondecreasing switching curve in the number of type-1 jobs. We characterize the necessary and sufficient conditions under which each policy will be optimal. We also explore the use of the optimal policy for the problem with no arrivals as a heuristic for the problem with dynamic arrivals.

scholarly journals MAP+MAP/M2/N/∞Queueing System with Absolute Priority and Reservation of Servers

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Bin Sun ◽  
Moon Ho Lee ◽  
Alexander N. Dudin ◽  
Sergey A. Dudin
Keyword(s):  
Time Distribution ◽  
Queueing System ◽  
Waiting Time Distribution ◽  
Stieltjes Transform ◽  
Absolute Priority ◽  
Arrival Processes ◽  
System States ◽  
Multiserver Queueing System

We consider a multiserver queueing system with an infinite buffer and two types of customers. The flow of customers is described by two Markovian arrival processes (MAPs). Type 1 customers have absolute priority over type 2 customers. If the arriving type 1 customer encounters all servers busy, but some of them provide service to type 2 customers, service of one type 2 customer is terminated and type 1 customer occupies the released server. To avoid too frequent termination of service of type 2 customers, we suggest reservation of some number of servers for type 1 customers. Type 2 customers, who do not succeed to get a server upon arrival or are knocked out from a server, join the buffer or leave the system forever. During a waiting period in the buffer, type 2 customers can be impatient and may leave the system forever. The ergodicity condition of the system is derived in an analytically tractable form. The stationary distribution of the system states and the main performance measures are calculated. The Laplace-Stieltjes transform of the waiting time distribution of an arbitrary type 2 customer is derived. Numerical examples are presented. The problem of the optimal channel reservation is numerically solved.

scholarly journals Queueing System with Heterogeneous Customers as a Model of a Call Center with a Call-Back for Lost Customers

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Sergey Dudin ◽  
Chesoong Kim ◽  
Olga Dudina ◽  
Janghyun Baek
Keyword(s):  
Call Center ◽  
Queueing System ◽  
Optimal Choice ◽  
Arrival Process ◽  
Finite Buffers ◽  
Different Types ◽  
Sojourn Time Distribution ◽  
Multiserver Queueing System

A multiserver queueing system with infinite and finite buffers, two types of customers, and two types of servers as a model of a call center with a call-back for lost customers is investigated. Type 1 customers arrive to the system according to a Markovian arrival process. All rejected type 1 customers become type 2 customers. Typer,r=1,2, servers serve typercustomers if there are any in the system and serve typer′,r′=1,2,  r′≠r,customers if there are no typercustomers in the system. The service times of different types of customers have an exponential distribution with different parameters. The steady-state distribution of the system is analyzed. Some key performance measures are calculated. The Laplace-Stieltjes transform of the sojourn time distribution of type 2 customers is derived. The problem of optimal choice of the number of each type servers is solved numerically.

scholarly journals A Queueing System with Heterogeneous Impatient Customers and Consumable Additional Items

2017 ◽  
Vol 27 (2) ◽  
pp. 367-384 ◽  
Author(s):  
Janghyun Baek ◽  
Olga Dudina ◽  
Chesoong Kim
Keyword(s):  
Waiting Time ◽  
Queueing System ◽  
Optimization Problems ◽  
Markovian Arrival Process ◽  
Arrival Process ◽  
Single Server ◽  
Finite Buffer ◽  
Threshold Strategy

Abstract A single-server queueing system with a marked Markovian arrival process of heterogeneous customers is considered. Type-1 customers have limited preemptive priority over type-2 customers. There is an infinite buffer for type-2 customers and no buffer for type-1 customers. There is also a finite buffer (stock) for consumable additional items (semi-products, half-stocks, etc.) which arrive according to the Markovian arrival process. Service of a customer requires a fixed number of consumable additional items depending on the type of the customer. The service time has a phase-type distribution depending on the type of the customer. Customers in the buffer are impatient and may leave the system without service after an exponentially distributed amount of waiting time. Aiming to minimize the loss probability of type-1 customers and maximize throughput of the system, a threshold strategy of admission to service of type-2 customers is offered. Service of type-2 customer can start only if the server is idle and the number of consumable additional items in the stock exceeds the fixed threshold. Stationary distributions of the system states and the waiting time are computed. In the numerical example, we show some interesting effects and illustrate a possibility of application of the presented results for solution of optimization problems.

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