Please use this identifier to cite or link to this item:
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Author(s): Reid, Kenneth Neil
Li, Jingpeng
Swan, Jerry
McCormick, Alistair
Owusu, Gilbert
Contact Email:
Title: Variable Neighbourhood Search: A Case Study for a Highly-Constrained Workforce Scheduling Problem
Citation: Reid KN, Li J, Swan J, McCormick A & Owusu G (2016) Variable Neighbourhood Search: A Case Study for a Highly-Constrained Workforce Scheduling Problem. In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE SSCI 2016: IEEE Symposium Series on Computational Intelligence, Athens, Greece, 06.12.2016-09.12.2016. Piscataway, NJ, USA: IEEE.
Issue Date: 31-Dec-2016
Conference Name: IEEE SSCI 2016: IEEE Symposium Series on Computational Intelligence
Conference Dates: 2016-12-06 - 2016-12-09
Conference Location: Athens, Greece
Abstract: This paper describes a Variable Neighbourhood Search (VNS) combined with simulated annealing to tackle a highly constrained workforce scheduling problem at British Telecommunications plc (BT). A refined greedy algorithm is firstly designed to create an initial solution which meets all hard constraints and satisfies some of the soft constraints. The VNS is then used to swap out less promising combinations, continually moving towards a more optimal solution until meeting finishing requirements. The results are promising when compared to the stand- alone greedy algorithm. We believe there is scope for this to be extended in several ways, i.e. into a more complex variation of VNS to further improve results, to be applied to further data sets and workforce scheduling problem scenarios, and to have input parameters to the algorithm selectively optimized to discover what kind of improvements in efficiency and fitness are possible. There is also scope for this to be used in similar combinatorial optimization problems.
Status: AM - Accepted Manuscript
Rights: Accepted for publication in a forthcoming proceedings to be published by IEEE. © 2016 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 
KenReidUniversityOfStirling.pdfFulltext - Accepted Version782.08 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 providing details and we will remove the Work from public display in STORRE and investigate your claim.