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Conference Proceeding

Shift Scheduling and Employee Rostering: An Evolutionary Ruin & Stochastic Recreate Solution

Citation
Reid KN, Li J, Veerapen N, Swan J, Mccormick A, Kern M & Owusu G (2019) Shift Scheduling and Employee Rostering: An Evolutionary Ruin & Stochastic Recreate Solution. In: 2018 10th Computer Science and Electronic Engineering (CEEC). 10th Computer Science and Electronic Engineering Conference (CEEC), Colchester, 19.09.2018-21.09.2018. Piscataway, NJ, USA: IEEE, pp. 19-23. https://doi.org/10.1109/CEEC.2018.8674200

Abstract
For decades, since the inception of the field, scheduling problems have been solved with a variety of techniques. Many proven algorithms to these problems exist; however, there is no single method to solve all the vast variety of problems that exist across many sub-fields with differing datasets. In this paper we explore the use of an Evolutionary Ruin & Stochastic Recreate algorithm, with a Simulated Annealing control mechanism, to a real-world employee scheduling problem and its ability to solve this problem to near optimality. The combinatorial possibilities of parameterisation are very large-the Taguchi design of experiments method is used to examine a subset of those possibilities within a limited runtime budget. Evolutionary Ruin and Stochastic Recreate has not previously been applied to the specific scheduling domain of employee scheduling and rostering: we investigate the effectiveness of the algorithm with different parameter values and discuss the insight it provides into the runtime effect of the mechanisms of Evolutionary Ruin & Stochastic Recreate.

Keywords
Evolutionary Ruin and Stochastic Recreate, Metaheuristics, Employee Rostering, Shift Scheduling, Monte-Carlo Acceptance, Taguchi Design of Experiments,Taguchi Method

StatusPublished
Author(s)Reid, Kenneth N; Li, Jingpeng; Veerapen, Nadarajen; Swan, Jerry; Mccormick, Alistair; Kern, Mathias; Owusu, Gilbert
FundersEPSRC Engineering and Physical Sciences Research Council
Publication date31/12/2019
Publication date online28/03/2019
URLhttp://hdl.handle.net/1893/29185
PublisherIEEE
Place of publicationPiscataway, NJ, USA
eISBN978-1-5386-7275-4
Conference10th Computer Science and Electronic Engineering Conference (CEEC)
Conference locationColchester
Dates
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