Real-Life Optimum Shift Scheduling Design
DOI:
https://doi.org/10.5614/itbj.ict.res.appl.2019.13.1.2Keywords:
criteria-based, heuristic algorithm, minimum manpower, random pick, shift design, shift scheduling, shift starting time, two-stage schedulingAbstract
In many industries, manpower shift scheduling poses problems that require immediate solutions. The fundamental need in this domain is to ensure that all shifts are assigned to cover all or as many jobs as possible. The shifts should additionally be planned with minimum manpower utilization, minimum manpower idleness and enhanced adaptability of employee schedules. The approach used in this study was to utilize an existing manpower prediction method to decide the minimum manpower required to complete all jobs. Based on the minimum manpower number and shift criteria, the shifts were assigned to form schedules using random pick and criteria-based selection methods. The potential schedules were then optimized and the best ones selected. Based on several realistic test instances, the proposed heuristic approach appears to offer promising solutions for shift scheduling as it improves shift idle time, complies with better shift starting time and significantly reduces the manpower needed and the time spent on creating schedules, regardless of data size.Downloads
References
Anbil R., Gelman, E., Patty B. & Tanga, R., Recent Advances in Crew-pairing Optimization at American Airlines, Interfaces, 21(1), pp. 62-74, 1991.
Lau. H.C., On the Complexity of Manpower Shift Scheduling, Computers & Operations Research, 23(1), pp. 93-102, 1996.
Heimerl, C. & Kolisch, R., Scheduling and Staffing Multiple Projects with a Multi-skilled Workforce, OR Spectrum, 32(2), pp. 343-368, 2010.
Van den Bergh, J., Beli<
Ernst, A.T., Jiang, H., Krishnamoorthy, M. & Sier, D., Staff Scheduling and Rostering: A Review of Applications, Methods and Models, European Journal of Operational Research, 153(1), pp. 3-27, 2004.
Lin, C.K.Y., Lai, K.F. & Hung, S.L., Development of a Workforce Management System for a Customer Hotline Service, Computers & Operations Research, 27(10), pp. 987-1004, 2000.
Shahnazari-Shahrezaei, P., Tavakkoli-Moghaddam, R. & Kazemipoor, H., Solving a New Fuzzy Multi-Objective Model for a Multi-Skilled Manpower Scheduling Problem by Particle Swarm Optimization and Elite Tabu Search, International Journal of Advanced Manufacturing Technology, 64(9-12), pp. 1517-1540, 2013.
Di Gaspero, L., Gartner, J., Musliu, N., Schaerf A., Schafhauser, W. & Slany, W., A Hybrid LS-CP Solver for the Shifts and Breaks Design Problem, Hybrid Metaheuristics Lecture Notes in Computer Science (Vol. 6373), M.J. Blesa, C. Blum, G, Raidl, A. Roli, M. Sampels, eds, Springer, 2010.
Ho, S.C. & Leung, J.M.Y, Solving a Manpower Scheduling Problem for Airline Catering using Metaheuristics, European Journal of Operational Research, 202(3), pp. 903-921, 2010.
Naudin, ., Chan, P.Y.C., Hiroux, M., Zemmouri, T. & Weil, G., Analysis of Three Mathematical Models of the Staff Rostering Problem. Journal of Scheduling, 15(1), pp. 23-38, 2012.
sgeirsson, E.I., Kyngas, J., Nurmi, K. & St",levik, M., A Framework for Implementation-Oriented Staff Scheduling, 5th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA), Phoenix, Arizona, USA, 2011.
Sze, S.N., Chiew, K.L. & Sze, J.F., Multi-Trip Vehicle Routing and Scheduling Problem with Time Window in Real Life, Numerical Analysis and Applied Mathematics ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics, AIP Conference Proceedings 1479, pp. 1151-1154, 2012.
Kim, S.J., Ko, Y.W., Uhmn, S. & Kim, J., A Strategy to Improve Performance of Genetic Algorithm for Nurse Scheduling Problem, International Journal of Software Engineering and Its Applications, 8(1), pp. 53-62, 2014.
Leksakul, K. & Phetsawat, S., Nurse Scheduling using Genetic Algorithm. Mathematical Problems in Engineering, 2014, 2014.
Pinheiro, R.L., Landa-Silva, D. & Atkin, J., A Variable Neighbourhood Search for the Workforce Scheduling and Routing Problem, In Advances in Nature and Biologically Inspired Computing, Proceedings of the 7th World Congress on Nature and Biologically Inspired Computing, NaBIC2015, Advances in Intelligent Systems and Computing, 419, pp. 247-259, 2015.
Rahimian, E., Akartunali, K. & Levine, J., A Hybrid Integer and Constraint Programming Approach to Solve Nurse Rostering Problems, Computers & Operations Research, 82, pp. 83-94, 2017.
Volland, J., F1/4gener, A. & Brunner, J.O., A Column Generation Approach for the Integrated Shift and Task Scheduling Problem of Logistics Assistants in Hospitals, European Journal of Operational Research, 260(1), pp. 316-334, 2017.
