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.
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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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