Abdallah, N. (2025). Optimizing Multi-Skill Call Center Performance: A Queuing Model Approach to Staffing and Service Level Management. Bulletin of Faculty of Science, Zagazig University, 2024(4), 57-63. doi: 10.21608/bfszu.2024.270134.1365
N. M. S. Abdallah. "Optimizing Multi-Skill Call Center Performance: A Queuing Model Approach to Staffing and Service Level Management". Bulletin of Faculty of Science, Zagazig University, 2024, 4, 2025, 57-63. doi: 10.21608/bfszu.2024.270134.1365
Abdallah, N. (2025). 'Optimizing Multi-Skill Call Center Performance: A Queuing Model Approach to Staffing and Service Level Management', Bulletin of Faculty of Science, Zagazig University, 2024(4), pp. 57-63. doi: 10.21608/bfszu.2024.270134.1365
Abdallah, N. Optimizing Multi-Skill Call Center Performance: A Queuing Model Approach to Staffing and Service Level Management. Bulletin of Faculty of Science, Zagazig University, 2025; 2024(4): 57-63. doi: 10.21608/bfszu.2024.270134.1365
Optimizing Multi-Skill Call Center Performance: A Queuing Model Approach to Staffing and Service Level Management
In the realm of call centers, queuing models offer a valuable framework for analysis. In these models, customers are represented as callers, while servers take the form of call agents. Achieving an effective balance between service level and service costs is paramount for a call center's success, given the critical importance of service quality. This necessitates ensuring an adequate number of skilled agents at all times, a challenge commonly referred to as the staffing problem. This paper aims to elucidate the application of the queuing model in evaluating the performance of the multi-skilled call center and determining the optimal number of agents in each group. Also, an algorithm is adopted to solve the staffing model. Through a numerical example, we compute the steady-state probabilities, the service levels, the optimal number of agents in each group, and the minimum cost associated with the service level requirements to show the influential factors within the system.