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189431

Staffing Optimization Problem Based On Queueing Models Of Multi-Skill Call Center With Patient Customers

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Last updated: 28 Dec 2024

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Abstract

The call center considers an interesting area of the application of queueing models. In a call center's queueing model, the customers are the callers and the servers are the call agents. The call center, which effectively running must get to the balance between service level and service costs. The quality of the service presented is of essential importance. So, the call center must guarantee at any time an appropriate number of servers with appropriate multi-skills according to the expected level of the demand, this issue is ordinarily called the staffing problem. Thus , the paper has the aim to explain how to apply the queueing model method for evaluating the performance of multi-skill call center's index and computing the formula of service level through presenting the optimization of the staffing problem for the optimal number of agents in each group. Finally, we used the deduced results through a numerical example to calculate the steady- state probabilities, service levels, the optimal number of agents in each group, performance measures, and how these influence factors in the whole system.

DOI

10.21608/esju.2020.189431

Keywords

Queueing model, Multi-Skill Call Center, Steady- State Probabilities, Service Levels, Staffing Problem, Performance measures

Volume

64

Article Issue

2

Related Issue

26947

Issue Date

2020-12-01

Receive Date

2021-08-15

Publish Date

2020-12-01

Page Start

27

Page End

37

Print ISSN

0542-1748

Online ISSN

2786-0086

Link

https://esju.journals.ekb.eg/article_189431.html

Detail API

https://esju.journals.ekb.eg/service?article_code=189431

Order

2

Type

Original Article

Type Code

1,914

Publication Type

Journal

Publication Title

The Egyptian Statistical Journal

Publication Link

https://esju.journals.ekb.eg/

MainTitle

Staffing Optimization Problem Based On Queueing Models Of Multi-Skill Call Center With Patient Customers

Details

Type

Article

Created At

23 Jan 2023