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Dynamic Call Center Routing Policies Using Call Waiting and Agent Idle Times

Author

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  • Wyean Chan

    (Département d'informatique et de recherche opérationnelle (DIRO), Université de Montréal, Montréal, Québec H3C 3J7, Canada)

  • Ger Koole

    (Department of Mathematics, VU University Amsterdam, 1081 HV Amsterdam, The Netherlands)

  • Pierre L'Ecuyer

    (Département d'informatique et de recherche opérationnelle (DIRO), Université de Montréal, Montréal, Québec H3C 3J7, Canada)

Abstract

We study call routing policies for call centers with multiple call types and multiple agent groups. We introduce new weight-based routing policies where each pair (call type, agent group) is given a matching priority defined as an affine combination of the longest waiting time for that call type and the longest idle time or the number of idle agents in that agent group. The coefficients in this combination are parameters to be optimized. This type of policy is more flexible than traditional ones found in practice, and it performs better in many situations. We consider objective functions that account for the service levels, the abandonment ratios, and the fairness of occupancy across agent groups. We select the parameters of all considered policies via simulation-based optimization heuristics. This requires only the availability of a simulation model of the call center, which can be much more detailed and realistic than the models used elsewhere in the literature to study the optimality of certain types of routing rules. We offer a first numerical study of realistic routing rules that takes into account the complexity of real-life call centers.

Suggested Citation

  • Wyean Chan & Ger Koole & Pierre L'Ecuyer, 2014. "Dynamic Call Center Routing Policies Using Call Waiting and Agent Idle Times," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 544-560, October.
    • Handle: RePEc:inm:ormsom:v:16:y:2014:i:4:p:544-560
    DOI: 10.1287/msom.2014.0493
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    Cited by:

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    2. Siqiao Li & Ger Koole & Xiaolan Xie, 2020. "An adaptive priority policy for radiotherapy scheduling," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 154-180, March.
    3. Tien Thanh Dam & Thuy Anh Ta & Tien Mai, 2022. "Joint chance-constrained staffing optimization in multi-skill call centers," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 354-378, August.
    4. Xu Sun & Ward Whitt, 2018. "Creating Work Breaks from Available Idleness," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 721-736, October.
    5. Ibrahim, Rouba & L’Ecuyer, Pierre & Shen, Haipeng & Thiongane, Mamadou, 2016. "Inter-dependent, heterogeneous, and time-varying service-time distributions in call centers," European Journal of Operational Research, Elsevier, vol. 250(2), pages 480-492.
    6. Wu, Xueqi & Zhou, Shenghai, 2022. "Sequencing and scheduling appointments on multiple servers with stochastic service durations and customer arrivals," Omega, Elsevier, vol. 106(C).
    7. Seung Bum Soh & Itai Gurvich, 2017. "Call Center Staffing: Service-Level Constraints and Index Priorities," Operations Research, INFORMS, vol. 65(2), pages 537-555, April.
    8. Ta, Thuy Anh & Chan, Wyean & Bastin, Fabian & L’Ecuyer, Pierre, 2021. "A simulation-based decomposition approach for two-stage staffing optimization in call centers under arrival rate uncertainty," European Journal of Operational Research, Elsevier, vol. 293(3), pages 966-979.

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