Integer Programming Model in Handling IT Incident Workload

##plugins.themes.bootstrap3.article.main##

Mohd Nizamuddin Abas
Siti Haida Ismail
Haslaile Abdullah

Abstract

A system called Incident Ticket System (ITS) uses in an organization to identify issue about service failure of IT system. The IT support personnel or team is responsible to resolve an incident associated with the ticket. The ticket has different kind of complexity which takes different time to solve and different level of expertise to close it. Therefore, allocating the optimum quantity of tickets to the right team members is vital in order to close all ticket at minimum time. Balancing the amount of ticket that each team member should get respectively with the ticket severity is important. To make even-handed workload for each team member, an approach of Integer Programming (IP) was applied in allocating the IT incident ticket. The IP model was implemented in Microsoft Excel software by using SOLVER. The computational results show that the proposed IP model was capable on solving allocation of ticket-severity problem.

##plugins.themes.bootstrap3.article.details##

How to Cite
Abas, M. N., Ismail, S. H., & Abdullah, H. . (2021). Integer Programming Model in Handling IT Incident Workload. International Journal of Applied Business and Information Systems, 4(1), 107–111. https://doi.org/10.31763/ijabis.v4i1.441
Section
Articles

References

Marcu, P., Grabarnik, G., Luan, L., Rosu, D., Shwartz, L., & Ward, C. (2009). Towards an optimized model of incident ticket correlation. Paper presented at the 2009 IFIP/IEEE International Symposium on Integrated Network Management.

Leblebici, D. (2012). Impact of workplace quality on employee’s productivity: case study of a bank in Turkey. Journal of Business, Economics, 1(1), 38-49.

Hom, P. W., Lee, T. W., Shaw, J. D., & Hausknecht, J. P. (2017). One hundred years of employee turnover theory and research. Journal of applied psychology, 102(3), 530.

Lu, L., Lu, A. C. C., Gursoy, D., & Neale, N. R. (2016). Work engagement, job satisfaction, and turnover intentions. International Journal of Contemporary Hospitality Management.

Santos, H. G., Toffolo, T. A., Gomes, R. A., & Ribas, S. (2016). Integer programming techniques for the nurse rostering problem. Annals of Operations Research, 239(1), 225-251.

Valouxis, C., Gogos, C., Goulas, G., Alefragis, P., & Housos, E. (2012). A systematic two phase approach for the nurse rostering problem. European Journal of Operational Research, 219(2), 425-433.

Ku, W.-Y., Pinheiro, T., & Beck, J. C. (2014). CIP and MIQP models for the load balancing nurse-to-patient assignment problem. Paper presented at the International Conference on Principles and Practice of Constraint Programming.

Mullinax, C., & Lawley, M. (2002). Assigning patients to nurses in neonatal intensive care. Journal of the operational research society, 53(1), 25-35.

Pesant, G. (2016). Balancing nursing workload by constraint programming. Paper presented at the International Conference on AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems.

Labidi, M., Mrad, M., Gharbi, A., & Louly, M. (2014). Scheduling IT staff at a bank: a mathematical programming approach. The Scientific World Journal, 2014.

Ryan, D., & Foster, E. (1981). Rn integer programming approach to scheduling.

Wang, T., Meskens, N., & Duvivier, D. (2015). Scheduling operating theatres: Mixed integer programming vs. constraint programming. European Journal of Operational Research, 247(2), 401-413.

Beyer, H. L., Dujardin, Y., Watts, M. E., & Possingham, H. P. (2016). Solving conservation planning problems with integer linear programming. Ecological Modelling, 328, 14-22.

Ku, W.-Y., & Beck, J. C. (2016). Mixed integer programming models for job shop scheduling: A computational analysis. Computers & Operations Research, 73, 165-173.

Ozlen, M., Burton, B. A., & MacRae, C. A. (2014). Multi-objective integer programming: An improved recursive algorithm. Journal of Optimization Theory and Applications, 160(2), 470-482.