Optimal balanced control for call centers

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In this paper we study the optimal assignment of tasks to agents in a call center. For this type of problem, typically, no single deterministic and stationary (i. e., state independent and easily implementable) policy yields the optimal control, and mixed strategies are used. Other than finding the optimal mixed strategy, we propose to optimize the performance over the set of "balanced" deterministic periodic non-stationary policies. We provide a stochastic approximation algorithm that allows to find the optimal balanced policy by means of Monte Carlo simulation. As illustrated by numerical examples, the optimal balanced policy outperforms the optimal mixed strategy. © 2012 Springer Science+Business Media, LLC.
LanguageEnglish
Pages39-62
JournalAnnals of Operations Research
Volume201
Issue number1
DOIs
StatePublished - 2012

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Call centres
Mixed strategy
Control strategy
Optimal control
Assignment
Monte Carlo simulation
Stochastic approximation
Approximation algorithms

Cite this

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title = "Optimal balanced control for call centers",
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author = "S. Bhulai and T. Yuan and B.F. Heidergott and {van der Laan}, D.A.",
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Optimal balanced control for call centers. / Bhulai, S.; Yuan, T.; Heidergott, B.F.; van der Laan, D.A.

In: Annals of Operations Research, Vol. 201, No. 1, 2012, p. 39-62.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Optimal balanced control for call centers

AU - Bhulai,S.

AU - Yuan,T.

AU - Heidergott,B.F.

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N2 - In this paper we study the optimal assignment of tasks to agents in a call center. For this type of problem, typically, no single deterministic and stationary (i. e., state independent and easily implementable) policy yields the optimal control, and mixed strategies are used. Other than finding the optimal mixed strategy, we propose to optimize the performance over the set of "balanced" deterministic periodic non-stationary policies. We provide a stochastic approximation algorithm that allows to find the optimal balanced policy by means of Monte Carlo simulation. As illustrated by numerical examples, the optimal balanced policy outperforms the optimal mixed strategy. © 2012 Springer Science+Business Media, LLC.

AB - In this paper we study the optimal assignment of tasks to agents in a call center. For this type of problem, typically, no single deterministic and stationary (i. e., state independent and easily implementable) policy yields the optimal control, and mixed strategies are used. Other than finding the optimal mixed strategy, we propose to optimize the performance over the set of "balanced" deterministic periodic non-stationary policies. We provide a stochastic approximation algorithm that allows to find the optimal balanced policy by means of Monte Carlo simulation. As illustrated by numerical examples, the optimal balanced policy outperforms the optimal mixed strategy. © 2012 Springer Science+Business Media, LLC.

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JO - Annals of Operations Research

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