• 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