Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29185
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Reid, Kenneth N
Li, Jingpeng
Veerapen, Nadarajen
Swan, Jerry
Mccormick, Alistair
Kern, Mathias
Owusu, Gilbert
Title: 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
Issue Date: 2019
Conference Name: 10th Computer Science and Electronic Engineering Conference (CEEC)
Conference Dates: 2018-09-19 - 2018-09-21
Conference Location: Colchester
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.
Status: AM - Accepted Manuscript
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Files in This Item:
File Description SizeFormat 
Paper2.pdfFulltext - Accepted Version345.52 kBAdobe PDFView/Open



This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.