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Article Dans Une Revue Computers & Industrial Engineering Année : 2016

A joint chance-constrained programming approach for call center workforce scheduling under uncertain call arrival forecasts

Résumé

A joint chance-constrained programming approach for call center workforce scheduling under uncertain call arrival forecasts Abstract We consider a workforce management problem arising in call centers, namely the shift-scheduling problem. It consists in determining the number of agents to be assigned to a set of predefined shifts so as to optimize the trade-off between manpower cost and customer quality of service. We focus on explicitly taking into account in the shift-scheduling problem the uncertainties in the future call arrival rates forecasts. We model them as independent random variables following a continuous probability distribution. The resulting stochastic optimization problem is handled as a joint chance-constrained program and is reformulated as an equivalent large-size mixed-integer linear program. One key point of the proposed solution approach is that this re-formulation is achieved without resorting to a scenario generation procedure to discretize the continuous probability distributions. Our computational results show that the proposed approach can efficiently solve real-size instances of the problem, enabling us to draw some useful managerial insights on the underlying risk-cost trade-off.
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Dates et versions

hal-01294589 , version 1 (29-03-2016)

Identifiants

Citer

M. Excoffier, C. Gicquel, O. Jouini. A joint chance-constrained programming approach for call center workforce scheduling under uncertain call arrival forecasts. Computers & Industrial Engineering, 2016, 96, pp.16-30. ⟨10.1016/j.cie.2016.03.013⟩. ⟨hal-01294589⟩
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