• Login
• Admin

Aickelin, Uwe, Li, Jingpeng and Burke, Edmund (2009) An evolutionary squeaky wheel optimisation approach to personnel scheduling. IEEE Transactions on Evolutionary Computation, 13 (2). pp. 433-443. ISSN 1089-778X

Full text not available from this repository.

Abstract

The quest for robust heuristics that are able to solve more than one problem is ongoing. In this paper, we present, discuss and analyse a technique called Evolutionary Squeaky Wheel Optimisation and apply it to two different personnel scheduling problems. Evolutionary Squeaky Wheel Optimisation improves the original Squeaky Wheel Optimisation’s effectiveness and execution speed by incorporating two additional steps (Selection and Mutation) for added evolution. In the Evolutionary Squeaky Wheel Optimisation, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping

conditions are reached. The aim of the Analysis step is to identify below average solution components by calculating a fitness value for all components. The Selection step then chooses amongst these underperformers and discards some

probabilistically based on fitness. The Mutation step further discards a few components at random. Solutions can become incomplete and thus repairs may be required. The repair is carried out by using the Prioritization step to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, improvements in the

Evolutionary Squeaky Wheel Optimisation is achieved by selective solution disruption mixed with iterative improvement and constructive repair. Strong experimental results are reported on two different domains of personnel scheduling: bus and rail driver scheduling and hospital nurse scheduling.

Item Type:	Article
RIS ID:	https://nottingham-repository.worktribe.com/output/1013829
Additional Information:	"©20xx IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."
Schools/Departments:	University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number:	10.1109/TEVC.2008.2004262
Depositing User:	Aickelin, Professor Uwe
Date Deposited:	15 Mar 2010 10:24
Last Modified:	04 May 2020 20:26
URI:	https://eprints.nottingham.ac.uk/id/eprint/1238

Actions (Archive Staff Only)

Edit View