A Hybrid Metaheuristic Approach to a Real World Employee Scheduling Problem - Archive ouverte HAL Access content directly
Conference Papers Year : 2019

A Hybrid Metaheuristic Approach to a Real World Employee Scheduling Problem

Abstract

Employee scheduling problems are of critical importance to large businesses. These problems are hard to solve due to large numbers of conflicting constraints. While many approaches address a subset of these constraints, there is no single approach for simultaneously addressing all of them. We hybridise ‘Evolutionary Ruin & Stochastic Recreate’ and ‘Variable Neighbourhood Search’ metaheuristics to solve a real world instance of the employee scheduling problem to near optimality. We compare this with Simulated Annealing, exploring the algorithm configuration space using the irace software package to ensure fair comparison. The hybrid algorithm generates schedules that reduce unmet demand by over 28% compared to the baseline. All data used, where possible, is either directly from the real world engineer scheduling operation of around 25,000 employees, or synthesised from a related distribution where data is unavailable.
Fichier principal
Vignette du fichier
Paper__3___Author_Copy.pdf (495.91 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02100461 , version 1 (21-11-2023)

Identifiers

Cite

Kenneth N. Reid, Jingpeng Li, Alexander E.I. Brownlee, Mathias Kern, Nadarajen Veerapen, et al.. A Hybrid Metaheuristic Approach to a Real World Employee Scheduling Problem. GECCO'19 (2019 Genetic and Evolutionary Computation Conference), ACM, Jul 2019, Prague, Czech Republic. ⟨10.1145/3321707.3321769⟩. ⟨hal-02100461⟩
196 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More