DocumentCode :
588718
Title :
Solving Call Center Agent Scheduling Problem through Improved Adaptive Genetic Algorithm
Author :
Yue Ma ; Lieli Liu
Author_Institution :
Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
Volume :
2
fYear :
2012
fDate :
28-29 Oct. 2012
Firstpage :
27
Lastpage :
30
Abstract :
With the emergence of call center and its wide applications in enterprises, the schedule of agents becomes a core problem for reasonably deploying the human resources in call center and improving the productive force of the call center. This study uses improved adaptive genetic algorithm (IAGA) to solve scheduling problem for a 24-hours call center. This paper builds a mathematical model to describe the constraints of the agent scheduling problem with the object for minimizing the gap between demand forecast and actual work volume in each time period. in order to solve the defects of existing search algorithm, this paper uses IAGA to get the optimal solution of the optimization problem. Satisfactorily, the simulation results have turned out that the method possesses a better solving effect in faster test speed.
Keywords :
call centres; genetic algorithms; scheduling; search problems; IAGA; call center agent scheduling problem; human resources; improved adaptive genetic algorithm; mathematical model; optimization problem; search algorithm; time 24 hour; Genetic algorithms; Genetics; Personnel; Schedules; Scheduling; Sociology; Statistics; adaptive genetic algorithm; call center; genetic algorithm; scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
Type :
conf
DOI :
10.1109/ISCID.2012.158
Filename :
6405557
Link To Document :
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