A hybrid integer programming and artificial bee colony algorithm for staff scheduling in call centers. (September 2022)

• Record Type: Journal Article
• Authors: Xu, Yue; Wang, Xiuli
• Is Part Of: Computers & industrial engineering. Volume 171(2022)
• Publication Date: 2022-09
• Subjects: Call centers -- Staff scheduling -- Hybrid algorithm -- Integer programming -- Artificial bee colony algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108312
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: The study firstly treats scheduling call centers with employees' preferences. A two-stage approach is tailored for solving the problem. Integer programing is embedded in the artificial bee colony algorithm. The proposed algorithm can obtain good solutions for the problem. Abstract: The staff scheduling problem (SSP) in call centers is defined as determining working/non-working days for a specific number of employees and their shift types in working days, considering service level requirements, some labor regulations and preferences. The SSP is often difficult to solve to optimality in practice for its complex structure. In this paper, a two-stage approach is proposed to tackle the problem, where the former generates preliminary solutions satisfying all the hard constraints, and the latter refines the solutions by fulfilling soft constraints as much as possible. The proposed approach employs artificial bee colony (ABC) algorithm as the main search framework in both stages, and appropriate neighborhood structures are designed respectively. Specifically, in the latter stage, integer programming (IP) employed under several ruin-and-recreate principles is embedded in the ABC algorithm, which helps intensify and diversify solutions. The experimental results show that the proposed approach is effective and efficient in achieving good solutions for large-scale problem instances. In addition, we give some guidance on how to weigh various employees' working preferences and how to balance labor costs and staff satisfaction. Finally, a case study is given to explain how the proposed model and algorithm work for a call center. This study will help call centers make appropriate decisions when planning their employees.