A logistic regression and linear programming approach for multi-skill staffing optimization in call centers
We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge lies in the fact that the QoS functions have no closed-form and need to be approximated by simulation. In thi...
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sg-smu-ink.sis_research-83112023-08-03T23:26:42Z A logistic regression and linear programming approach for multi-skill staffing optimization in call centers TA, Thuy Anh MAI, Tien BASTIN, Fabian l'ECUYER, Pierre We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge lies in the fact that the QoS functions have no closed-form and need to be approximated by simulation. In this paper we propose a new way to approximate the QoS functions by logistic functions and design a new algorithm that combines logistic regression, cut generations and logistic-based local search to efficiently find good staffing solutions. We report computational results using examples up to 65 call types and 89 agent groups showing that our approach performs well in practice, in terms of solution quality and computing time. 2022-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7308 info:doi/10.1109/WSC57314.2022.10015281 https://ink.library.smu.edu.sg/context/sis_research/article/8311/viewcontent/WSC2022_R2.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University logistic regression simulation call center cutting plane Artificial Intelligence and Robotics Programming Languages and Compilers |
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logistic regression simulation call center cutting plane Artificial Intelligence and Robotics Programming Languages and Compilers TA, Thuy Anh MAI, Tien BASTIN, Fabian l'ECUYER, Pierre A logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
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We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge lies in the fact that the QoS functions have no closed-form and need to be approximated by simulation. In this paper we propose a new way to approximate the QoS functions by logistic functions and design a new algorithm that combines logistic regression, cut generations and logistic-based local search to efficiently find good staffing solutions. We report computational results using examples up to 65 call types and 89 agent groups showing that our approach performs well in practice, in terms of solution quality and computing time. |
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text |
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TA, Thuy Anh MAI, Tien BASTIN, Fabian l'ECUYER, Pierre |
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TA, Thuy Anh MAI, Tien BASTIN, Fabian l'ECUYER, Pierre |
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TA, Thuy Anh |
title |
A logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
title_short |
A logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
title_full |
A logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
title_fullStr |
A logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
title_full_unstemmed |
A logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
title_sort |
logistic regression and linear programming approach for multi-skill staffing optimization in call centers |
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Institutional Knowledge at Singapore Management University |
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2022 |
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https://ink.library.smu.edu.sg/sis_research/7308 https://ink.library.smu.edu.sg/context/sis_research/article/8311/viewcontent/WSC2022_R2.pdf |
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