Results 1  10
of
48
Contact centers with a callback option and realtime delay information
 Operations Research
, 2004
"... doi 10.1287/opre.1030.0088 ..."
Queueing dynamics and maximal throughput scheduling in switched processing systems. Queueing systems
"... Abstract. We study a processing system comprised of parallel queues, whose individual service rates are specified by a global service mode (configuration). The issue is how to switch the system between various possible service modes, so as to maximize its throughput and maintain stability under the ..."
Abstract

Cited by 49 (15 self)
 Add to MetaCart
Abstract. We study a processing system comprised of parallel queues, whose individual service rates are specified by a global service mode (configuration). The issue is how to switch the system between various possible service modes, so as to maximize its throughput and maintain stability under the most workloadintensive input traffic traces (arrival processes). Stability preserves the job inflow–outflow balance at each queue on the traffic traces. Two key families of service policies are shown to maximize throughput, under the mild condition that traffic traces have longterm average workload rates. In the first family of cone policies, the service mode is chosen based on the system backlog state belonging to a corresponding cone. Two distinct policy classes of that nature are investigated, MaxProduct and FastEmpty. In the second family of batch policies (BatchAdapt), jobs are collectively scheduled over adaptively chosen horizons, according to an asymptotically optimal, robust schedule. The issues of nonpreemptive job processing and nonnegligible switching times between service modes are addressed. The analysis is extended to cover feedforward networks of such processing systems/nodes. The approach taken unifies and generalizes prior studies, by developing a general tracebased modeling framework (samplepath approach) for addressing the queueing stability problem. It treats the queueing structure as a deterministic dynamical system and analyzes directly its evolution trajectories. It does not require any probabilistic superstructure, which is
Performance Evaluation and Policy Selection in Multiclass Networks
, 2002
"... This paper concerns modelling and policy synthesis for regulation of multiclass queueing networks. A 2parameter network model is introduced to allow independent modelling of variability and mean processingrates, while maintaining simplicity of the model. Policy synthesis is based on consideration ..."
Abstract

Cited by 46 (26 self)
 Add to MetaCart
This paper concerns modelling and policy synthesis for regulation of multiclass queueing networks. A 2parameter network model is introduced to allow independent modelling of variability and mean processingrates, while maintaining simplicity of the model. Policy synthesis is based on consideration of more tractable workload models, and then translating a policy from this abstraction to the discrete network of interest. Translation is made possible through the use of safetystocks that maintain feasibility of workload trajectories. This is a wellknown approach in the queueing theory literature, and may be viewed as a generic approach to avoid deadlock in a discreteevent dynamical system. Simulation is used to evaluate a given policy, and to tune safetystock levels. These simulations are accelerated through a variance reduction technique that incorporates stochastic approximation to tune the variance reduction. The search for appropriate safetystock levels is coordinated through a cutting plane algorithm. Both the policy synthesis and the simulation acceleration rely heavily on the development of approximations to the value function through fluid model considerations.
A method for staffing large call centers based on stochastic fluid models
, 2004
"... We consider a call center model with m input flows and r pools of agents; the mvector λ of instantaneous arrival rates is allowed to be timedependent and to vary stochastically. Seeking to optimize the tradeoff between personnel costs and abandonment penalties, we develop and illustrate a practic ..."
Abstract

Cited by 40 (5 self)
 Add to MetaCart
(Show Context)
We consider a call center model with m input flows and r pools of agents; the mvector λ of instantaneous arrival rates is allowed to be timedependent and to vary stochastically. Seeking to optimize the tradeoff between personnel costs and abandonment penalties, we develop and illustrate a practical method for sizing the r agent pools. Using stochastic fluid models, this method reduces the staffing problem to a multidimensional newsvendor problem, which can be solved numerically by a combination of linear programming and Monte Carlo simulation. Numerical examples are presented, and in all cases the pool sizes derived by means of the proposed method are very close to optimal.
Heavy traffic analysis of open processing networks with complete resource pooling: asymptotic optimality of discrete review policies
 ANN. APPL. PROBAB
, 2005
"... We consider a class of open stochastic processing networks, with feedback routing and overlapping server capabilities, in heavy traffic. The networks ..."
Abstract

Cited by 25 (0 self)
 Add to MetaCart
(Show Context)
We consider a class of open stochastic processing networks, with feedback routing and overlapping server capabilities, in heavy traffic. The networks
From fluid relaxations to practical algorithms for job shop scheduling: the makespan objective
 Mathematical Programming
, 2002
"... We design an algorithm for the highmultiplicity jobshop scheduling problem with the objective of minimizing the total holding cost by appropriately rounding an optimal solution to a fluid relaxation in which we replace discrete jobs with the flow of a continuous fluid. The algorithm solves the flu ..."
Abstract

Cited by 23 (4 self)
 Add to MetaCart
(Show Context)
We design an algorithm for the highmultiplicity jobshop scheduling problem with the objective of minimizing the total holding cost by appropriately rounding an optimal solution to a fluid relaxation in which we replace discrete jobs with the flow of a continuous fluid. The algorithm solves the fluid relaxation optimally and then aims to keep the schedule in the discrete network close to the schedule given by the fluid relaxation. If the number of jobs from each type grow linearly with N,then the algorithm is within an additive factor O�N � from the optimal (which scales as O�N 2�); thus,it is asymptotically optimal. We report computational results on benchmark instances chosen from the OR library comparing the performance of the proposed algorithm and several commonly used heuristic methods. These results suggest that for problems of moderate to high multiplicity,the proposed algorithm outperforms these methods,and for very high multiplicity the overperformance is dramatic. For problems of low to moderate multiplicity,however,the relative errors of the heuristic methods are comparable to those of the proposed algorithm,and the best of these methods performs better overall than the proposed method. Received December 1999; revisions received July 2000,September 2001; accepted September 2002. Subject classifications: Production/scheduling,deterministic: approximation algorithms for deterministic job shops. Queues,optimization: asymptotically optimal solutions to queueing networks. Area of review: Manufacturing,Service,and Supply Chain Operations. 1.
DelayOptimal Opportunistic Scheduling And Approximations: The Log Rule
"... This paper considers the design of multiuser opportunistic packet schedulers for users sharing a timevarying wireless channel from performance and robustness points of view. For a simplified model falling in the classical Markov decision process framework, we numerically compute and characterize me ..."
Abstract

Cited by 19 (3 self)
 Add to MetaCart
This paper considers the design of multiuser opportunistic packet schedulers for users sharing a timevarying wireless channel from performance and robustness points of view. For a simplified model falling in the classical Markov decision process framework, we numerically compute and characterize meandelayoptimal scheduling policies. The computed policies exhibit radial sumrate monotonicity: as users ’ queues grow linearly, the scheduler allocates service in a manner that deemphasizes the balancing of unequal queues in favor of maximizing current system throughput (being opportunistic). This is in sharp contrast to previously proposed throughputoptimal policies, e.g., Exp rule and MaxWeight (with any positive exponent of queue length). In order to meet performance and robustness objectives, we propose a new class of policies, called the Log rule, that are radial sumrate monotone (RSM) and provably throughput optimal. In fact, it can also be shown that an RSM policy minimizes the asymptotic probability of sumqueue overflow. We use extensive simulations to explore various possible design objectives for opportunistic schedulers. When users see heterogenous channels, we find that emphasizing queue balancing, e.g. Exp rule and MaxWeight, may excessively compromise the overall delay. Finally, we discuss approaches to implement the proposed policies for scheduling and resource allocation in OFDMAbased multichannel systems.
Multiproduct systems with both setup times and costs: Fluid bounds and schedules
 Operations Research
, 2004
"... This paper considers a multiproduct, singleserver production system where both setup times and costs are incurred whenever the server changes product. The system is maketoorder with a per unit backlogging cost. The objective is to minimize the longrun average cost per unit time. Using a fluid m ..."
Abstract

Cited by 18 (0 self)
 Add to MetaCart
(Show Context)
This paper considers a multiproduct, singleserver production system where both setup times and costs are incurred whenever the server changes product. The system is maketoorder with a per unit backlogging cost. The objective is to minimize the longrun average cost per unit time. Using a fluid model, we provide a closedform lower bound on system performance. This bound is also shown to provide a lower bound for stochastic systems when scheduling is static, but is only an approximation when scheduling is dynamic. Heavytraffic analysis yields a refined bound that includes secondmoment terms. The fluid bound suggests both dynamic and static scheduling In this paper we consider a production environment where a number of different products are produced on a single machine and setup activities are necessary when switches of product type are made. These setup activities require both time and cost that depend on the specific product type. Throughout the paper we assume that the setups do not depend on the previous product produced