Abstract
Staff scheduling and planning in a cost effective manner has been a topic of scientific discussion for many years, driven by the need of many organisations to fully and effectively utilise their workforce to meet costumer demand and deliver service. Due to the varying nature of industry sectors, problems often require tailoring for particular business needs and types of work. This paper presents an overview of how a version of this problem was solved in a business with a large field workforce. The automation of this process has proved vital in ensuring that there is the right amount of resources rostered in on each day of the week, transforming a lengthy, manual procedure into an operation of a matter of seconds. The paper discusses how a Simulated Annealing approach was implemented, and provides a comparison of its performance versus a standard Hill Climber. We also include a detailed description of how rules and constraints were incorporated into the work, and what effect these had on rostered attendance.
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Notes
- 1.
Emphasis on specific areas to ensure targeted optimisation through the use of penalties/weights.
- 2.
The cost function is dependant on the different types of soft constraints.
- 3.
For example, a range of 10 on Saturday should not be considered the same as a range of 10 on any other day of the week due to the smaller number of attending resources.
- 4.
A “fixed” resource simply means that they cannot change start week.
- 5.
Note, some resources are only allowed certain start weeks due to constraints related to factors such as sub-cycles and consecutive Saturdays.
References
Barnhart, C., Cohn, A.M., Johnson, E.L., Klabjan, D., Nemhauser, G.L., Vance, P.H.: Airline crew scheduling. In: Hall, R.W. (ed.) Handbook of Transportation Science. International Series in Operations Research & Management Science, vol. 56, pp. 517–560. Springer, US (2003). https://doi.org/10.1007/0-306-48058-1_14
Brusco, M.J., Jacobs, L.W.: A simulated annealing approach to the cyclic staff-scheduling problem. Nav. Res. Logist. (NRL) 40(1), 69–84 (1993)
Burns, A., Hayes, N., Richardson, M.F.: Generating feasible cyclic schedules. Control Eng. Pract. 3(2), 151–162 (1995)
Caprara, A., Fischetti, M., Toth, P., Vigo, D., Guida, P.L.: Algorithms for railway crew management. Math. Program. 79, 125–141 (1997)
Cheang, B., Li, H., Lim, A., Rodrigues, B.: Nurse rostering problems - a bibliographic survey. Eur. J. Oper. Res. 151(3), 447–460 (2003)
Du, K.L., Swamy, M.N.S.: Search and Optimization by Metaheuristics: Techniques and Algorithms Inspired by Nature. Birkhäuser, Basel (2016)
Ernst, A., Krishnamoorthy, M., Dowling, D.: Train crew rostering using simulated annealing. In: Caccetta, L., Teo, K.L., Sieq, P.F., Leung, Y.H., Jennings, L.S., Rehbock, V. (eds.) Proceedings of International Conference on Optimisation Techniques and Applications, pp. 859–866 (1998)
Ernst, A.T., Jiang, H., Krishnamoorthy, M., Sier, D.: Staff scheduling and rostering: a review of applications, methods and models. Eur. J. Oper. Res. 153(1), 3–27 (2004)
Gonçalves, R., Gomide, F., Lagrimante, R.: Methodology and algorithms for railway crew management. IFAC Proc. Vol. 33(9), 323–328 (2000)
Hadwan, M., Ayob, M.: A constructive shift patterns approach with simulated annealing for nurse rostering problem. Proceedings of 2010 International Symposium on Information Technology - Visual Informatics, ITSim 2010, p. 1 (2010)
Kundu, S., Mahato, M., Mahanty, B., Acharyya, S.: Comparative performance of simulated annealing and genetic algorithm in solving nurse scheduling problem. In: Proceedings of the International MultiConference of Engineers and Computer Scientists, p. 1 (2008)
Thiel, M.P.: Team-oriented airline crew scheduling and rostering: problem description, solution approaches, and decision support. Ph.D. thesis, Faculty of Business Administration and Economics at the University of Paderborn, Germany (2005)
Thompson, G.M.: A simulated annealing heuristic for shift scheduling using non-continuously available employees. Comput. Oper. Res. 23(3), 275–288 (1996)
Valdes, V.A.V.: Integrating crew scheduling and rostering problems. Ph.D. thesis, Alma Mater Studiorum Universita di Bologna, Italy (2010)
Voudouris, C., Owusu, G., Dorne, R., Lesaint, D.: Service Chain Management: Technology Innovation for the Service Business. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-75504-3
Xie, L., Kliewer, N., Suhl, L.: Integrated driver rostering problem in public bus transit. Procedia Soc. Behav. Sci. 54, 656–665 (2012)
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Dimitropoulaki, M., Kern, M., Owusu, G., McCormick, A. (2018). Workforce Rostering via Metaheuristics. In: Bramer, M., Petridis, M. (eds) Artificial Intelligence XXXV. SGAI 2018. Lecture Notes in Computer Science(), vol 11311. Springer, Cham. https://doi.org/10.1007/978-3-030-04191-5_25
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