Resumen
This document studies one of the many applications and challenges that call centers face for staff scheduling. The objective of this document is to design and implement a solution technique that seeks to minimize costs due to missing teleoperators during lunch and breaks time for different operations of teleoperators with pre-defined shifts, reducing execution times and fulfilling the restrictions that each operation has. As part of the limitations identified for the development of this simulation, it was established that teleoperators have a defined shift with start and end time, according to the labor contract of each teleoperator, and the scenarios were simulated in 24-h operation as maximum, to guarantee one tool which responds to possible daily variations that may arise in different scenarios. In this context, genetic algorithm was proposed to provide a solution regarding to all requirements, achieving results near to the optimum. Besides, we defined the execution of four scenarios composed of operations with 200, 500, 2000 and 5000 teleoperators, each with different constraints and variables, to evaluate how the proposed algorithm responds. As result, solutions were generated with better performance in comparison with company’s actual scheduling model for lunch and break times, achieving on average a 42% decrease in total cost and 69% reduction in tool execution time. Also, we got better results for computational time in scenarios with 200 and 500 teleoperators, showing 76% less compared to current company’s tool, and for instances with more teleoperators (2000 and 5000), better results are presented with 60% reduction of costs delivered by the company’s tool.
Idioma original | Inglés |
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Título de la publicación alojada | Operations Research and Analytics in Latin America |
Editores | Jairo Montoya Torres, William Guerrero, David Cortes |
Editorial | Springer |
Páginas | 37–47 |
Número de páginas | 10 |
ISBN (versión digital) | 978-3-031-28870-8 |
ISBN (versión impresa) | 978-3-031-28869-2 |
DOI | |
Estado | Publicada - 05 oct. 2023 |