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OPTIMIZED PREFERENCE OF SECURITY STAFF SCHEDULING USING INTEGER LINEAR PROGRAMMING APPROACH

Shin Yin Ang, Siti Noor Asyikin Mohd Razali, Sie Long Kek

Abstract


This paper proposes an optimized schedule for security staff using integer linear programming approach. It is important to improve the life quality of the security staff since the negative social life such as family problems, less social support or even stress following from a poor work schedule. Therefore, this study aims to maximize the preference satisfaction of the security staff by allowing them to choose their preferred shift and day off while taking into consideration the restrictions of the university rules. The mathematical model of integer linear programming approach is developed and solved by using LPSolve IDE package. The result shows the overall preference satisfaction of the security staff towards work shift and days off is successfully maximized from 228.33 to 394.33. The comparison of the real schedule and the new proposed optimized schedule is made and all the constraints are successfully satisfied. The proposed schedule will be able to assist the university management in producing the most flexible and beneficial schedule for their staff to increase the satisfaction towards the working life.

Keywords


scheduling; shift; preference; integer programming; security staff

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References


Ernst, A.T., Jiang, H., Krishnamoorthy, M., Owens, B., & Sier, D. (2004). An annotated bibliography of personnel scheduling and rostering. Annals of Operations Research, 127(1-4), 21.

Meisels, A. & Schaerf, A. (2003) Modelling and solving employee timetabling problems. Annals of Mathematics and Artificial Intelligence, 39(1-2), 41-59.

Pinedo, M.L. (2005). Planning and Scheduling in Manufacturing and Services. Edition 1. Springer-Verlag New York, NY: Springer Series in operation research & financial engineering.

Nanda, R & Browne, J. (1992). Introduction to Employee Scheduling. New York: Van Nostrand Reinhold.

Lin CC., Kang JR., Liu WY. (2015) A Mathematical Model for Nurse Scheduling with Different Preference Ranks. In: Park J., Pan Y., Kim C., Yang Y. (eds) Future Information Technology - II. Lecture Notes in Electrical Engineering, vol 329. Springer, Dordrecht.

Ahasan, R., Khaleque, A. & Mohiuddin, G. (1999). Human aspects of shift work in developing countries: A case study in Bangladesh. Journal of Human Ergology, 28(1-2), 59-65.

Elizabeth A. Larson & Ruth Zemke (2003) Shaping the Temporal Patterns of our Lives: The Social Coordination of, Journal of Occupational Science, 10:2, 80-89, DOI: 10.1080/14427591.2003.9686514.

Topaloglu, S. & Selim, H. (2010). Nurse scheduling using fuzzy modeling approach. Fuzzy Sets and Systems, 161, 1543-1563.

Ajay, K.A. (2013). Modelistic Solution Approach For Flowshop Scheduling Problems On Makespan Criterion By Heuristics Models. Manav Bharti University, Solan, India.

Schaerf, A. (1999). A survey of automated timetabling (Review of the Artificial Intelligence Review a survey of automated timetabling). Artificial Intelligence Review, 13, 87-127.

Carter, M.W. & Laporte, G. (1996) Recent developments in practical examination timetabling. In: Burke E., Ross P. (eds) Practice and Theory of Automated Timetabling. PATAT 1995. Lecture Notes in Computer Science, 1153. Springer, Berlin, Heidelberg.

Nakasuwan, J., Srithip, P., & Komolavanij, S. (1). Class Scheduling Optimization. Science & Technology Asia, 4(2), 88-98. Retrieved from https://www.tci-thaijo.org/index.php/SciTechAsia/article/view/41949.

Mendoza, Adel & Jimenez Rojas, Ana & Hernández Escamilla, Sharon. (2017). Assigning schedules in the industrial engineering program at the Universidad Del Atlántico using linear programming. International Journal of Application or Innovation in Engineering & Management (IJAIEM). 6. 56-60.

Satheeshkumar, B., Nareshkumar, S. & Kumaraghuru, S. (2014). Linear Programming Applied to Nurses Shifting Problems. International Journal of Science and Research (IJSR), 3(3), ISSN: 2319-7064.

Ahmed Ali El Adoly, Mohamed Gheith & M. Nashat Fors. (2018). A new formulation and solution for the nurse scheduling problem: A case study in Egypt. Alexandria Engineering Journal. 57(4), Pages 2289-2298

Suryati Sitepu, Pasukat Sembiring, Herman Mawengkang. (2017). An Optimization Model for Integrated Capacity Management and Bed Allocation Planning of Hospitals. International Journal on Recent and Innovation Trends in Computing and Communication. 5(3), 169-173.

Mobasher Arezou, Lim Gino, Bard Jonathan & Jordan Victoria. (2011). Daily Scheduling of Nurses in Operating Suites. IIE Transactions on Healthcare Systems Engineering. 1(4). 232-246.

Ip W.H., Nick Chung & George Ho. (2010). Using Integer Programming for Airport Service Planning in Staff Scheduling. International Journal of Engineering Business Management. 2(2), 85-92.

Wan Nor Ashikin Wan Ahmad Fatthi, Adibah Shuib, Rosma Mohd Dom. A mixed integer programming model for solving real-time truck-to-door assignment and scheduling problem at cross docking warehouse. Journal of Industrial & Management Optimization, 2016, 12 (2) : 431-447. doi: 10.3934/jimo.2016.12.431.

Akanbi, Olumuyiwa O. (2016). Determination of the Optimal Cost of Training Staff in Tertiary Institution Using Linear Programming and Integer Linear Programming Model. The International Journal of Business &Management. 4(11), 87-93.

Seyed Hasan Hataminasab, Seyed Mohsen Mirjalili, Mahdieh Yavari & Mohamadreza Pakde. (2016). A Mathematical Model to Schedule Manpower and Solve using Genetic Algorithm. Pacific Business Review International. 1(4), 174-180.

Mahalakshmi E. &Akila S.. (2017). A shift sequence for job scheduling by using Linear programming problem. International Journal of Advanced in Management, Technology and Engineering Sciences. 7(12), 263-268.

Alfares, H.K., Lilly, M.T. & Emovon, I. (2007) Maintenance Staff Scheduling at Afam Power Station. IEMS, 6(1), 22-27.

Jafari H. & Salmasi N. (2015). Maximizing the nurses’ preferences in nurse scheduling problem: Mathematical modeling and a meta-heuristic algorithm. J. Ind. Eng. Int. 11, 439–458.

Thomas, P. I. (2013). Scheduling Algorithm with Optimization of Employee Satisfaction. Senior Design Project Article of Electrical and System Engineering Washington University.

Marti, R. & Reinelt, G. (2011). The Linear Ordering Problem, Exact and Heuristic Methods in Combinatorial Optimization. New York, NY: Springer Berlin Heidelberg

Pinedo, M.L. (2008). Scheduling: Theory, Algorithms, and Systems. New York, NY: Springer Science and Business Media.

Aladag, C.H. & Hocaoglu, G. (2007). A Tabu Search Algorithm To Solve A Course Timetabling Problem. Hacettepe Journal of Mathematics and Statistics, 36(1), 53-64.

Brezulianu, A., Fira, L. & Fira, M. (2012). A genetic algorithm approach for scheduling of resources in well-services companies. International Journal of Advanced Research in Artificial Intelligence (IJARAI), 1(5), 1-5.

Razali, S.N.A.M., Looi, M.F., Arbin, A. & Khamis, A. (2018). Integer linear programming on preference maximized of workforce scheduling. COMPUSOFT, An International Journal of Advanced Computer Technology, 7(11), 2320-0790.




DOI: http://dx.doi.org/10.6084/ijact.v8i4.854

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