Titre :

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

Auteur(s) :

Reid, Kenneth [Auteur]
University of Stirling
Li, Jingpeng [Auteur]
University of Stirling
Veerapen, Nadarajen [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Swan, Jerry [Auteur]
University of York [York, UK]
Mccormick, Alistair [Auteur]
Kern, Matthias [Auteur]
Owusu, Gilbert [Auteur]

Titre de la manifestation scientifique :

2018 10th Computer Science and Electronic Engineering (CEEC)

Organisateur(s) de la manifestation scientifique :

IEEE

Ville :

Colchester

Pays :

Royaume-Uni

Date de début de la manifestation scientifique :

2018-09-19

Titre de l’ouvrage :

Proceedings of the 2018 10th Computer Science and Electronic Engineering Conference (CEEC)

Éditeur :

IEEE

Mot(s)-clé(s) en anglais :

Resource management
Scheduling

Discipline(s) HAL :

Informatique [cs]/Intelligence artificielle [cs.AI]

Résumé en anglais : [en]

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 ...
Lire la suite >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 apply Evolutionary Ruin & Stochastic Recreate, equipped with a Exponential Monte Carlo acceptance criterion control mechanism, to a real-world employee scheduling problem. 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: the effect of different parameter values on runtime behaviour is investigated. The proposed approach is able to find close to optimal solutions to shift scheduling and employee rostering problems.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL