A mathematical model for personnel task assignment problem and an application for banking sector


Cetin K., TUZKAYA G., VAYVAY Ö.

International Journal of Optimization and Control: Theories and Applications, cilt.10, sa.2, ss.147-158, 2020 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 10 Sayı: 2
  • Basım Tarihi: 2020
  • Doi Numarası: 10.11121/ijocta.01.2020.00825
  • Dergi Adı: International Journal of Optimization and Control: Theories and Applications
  • Derginin Tarandığı İndeksler: Scopus, Academic Search Premier, Communication Abstracts, zbMATH, Directory of Open Access Journals, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.147-158
  • Anahtar Kelimeler: Analytical hierarchy process, Banking sector, Generalized assignment problem, Linear physical programming, Task assignment
  • Marmara Üniversitesi Adresli: Evet

Özet

© 2020 Balikesir University. All rights reserved.Efficient planning and management of the workforce resources is one of the most essential requirements for the companies operating in the service sector. For banks, a large number of transactions comes to Central Operations Department from the branches or directly from the customers and their aim is to provide the best operational service with the highest efficiency with the limited workforce resources in the departments. In this study, a real assignment problem was discussed and the problem was considered as Generalized Assignment Problem. For the solution of the problem, related algorithms were listed and examined in the literature survey section. Then, a two-step method is proposed. First step prioritizes the task coming to the system by considering the customer types, service level agreement (SLA) times, cut-off times, task type. In the second step, a multi-objective mathematical model was developed to assign task to employee groups. A preference based optimization method called Linear Physical Programming (LPP) is used to solve the model. Afterward, proposed model was tested on real banking data. For all the tests, GAMS was used as a solver. Results show that proposed model gave better results compared with current situation. With the proposed solution method, the workloads of the profile groups working above their capacity were transferred to other profile groups with idle capacity. Thus, the capacity utilization rates of the profile groups were more balanced and the minimum capacity utilization rate was calculated as 41%.