Optimal Shift Scheduling at Ibu Pejabat Polis Daerah (IPD) Kuala Muda using Goal Programming

Sharifah Fhahriyah Syed Abas; Jasmani  Bidin; Nurul Aatikah  Abdul

doi:10.24191/jcrinn.v6i3.219

Optimal Shift Scheduling at Ibu Pejabat Polis Daerah (IPD) Kuala Muda using Goal Programming

Authors

Sharifah Fhahriyah Syed Abas Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus
Jasmani Bidin Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus
Nurul Aatikah Abdul Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus

DOI:

https://doi.org/10.24191/jcrinn.v6i3.219

Keywords:

shifts, constraints, police officerâ€™s schedule, goal programming, Lingo software

Abstract

Many workplaces encounter complex problems in preparing an optimal work scheduling to meet the 24 hours work demand especially in shift working hours. The schedule needs to consider many constraints and multi objectives at the same time. A mathematical model such as Goal programming is able to cater this kind of problems. Thus, this study was designed to provide a systematic and optimal schedule for police officers at Criminal Unit, IPD Kuala Muda, Kedah. This study is aimed to formulate the best model for the shift rotating schedule of the police officers and to find the best way to optimize the police scheduling related to the limitations, requirements of the police station and the preferences of the police. Lingo software is used to run the model. However, only one out of three goals set for the study was achieved. The new schedule obtained shows that all police officers have the same number of working days, which is 21 days in the 28-day planning period. The new schedule produced is better than the previous manual schedule since it takes less time to prepare it without neglecting the constraints involved. To improve efficiency and flexibility on the generated schedules, it is recommended to use other methods such as hybrid swarm-based optimization and many new limitations and preferences should be also considered in the analysis.

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