Solving a stochastic queueing design and control problem with constraint programming

Authors:
Daria Terekhov;J. Christopher Beck;Kenneth N. Brown
Affiliations:
Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, Ontario, Canada;Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, Ontario, Canada;Cork Constraint Computation Centre, Department of Computer Science, University College Cork, Cork, Ireland
Venue:
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Year:
2007

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Abstract

A facility with front room and back room operations has the option of hiring specialized or, more expensive, cross-trained workers. Assuming stochastic customer arrival and service times, we seek a smallest-cost combination of cross-trained and specialized workers satisfying constraints on the expected customer waiting time and expected number of workers in the back room. A constraint programming approach using logic-based Benders' decomposition is presented. Experimental results demonstrate the strong performance of this approach across a wide variety of problem parameters. This paper provides one of the first links between queueing optimization problems and constraint programming.