Esra Gulmez
Heuristic and swarm intelligence algorithms for work-life balance problem
Gulmez, Esra; Koruca, Halil Ibrahim; Aydin, Mehmet Emin; Urganci, Kemal Burak
Authors
Halil Ibrahim Koruca
Dr Mehmet Aydin Mehmet.Aydin@uwe.ac.uk
Senior Lecturer in Networks and Mobile Computing
Kemal Burak Urganci
Abstract
Employee satisfaction significantly influences the success of business. This emphasises on the importance of employees managing their work, family and personal lives to maintain their physical and mental well-being. This is especially crucial in health-care sector, where physical and mental well-being directly affects the quality of out-coming services provided. Work-life balance, defined as the challenge of striking a reasonable equilibrium between work, family, and personal life, is gaining more attention. However, many studies do not adequately consider employee preferences when addressing this issue. This study introduces a mathematical model for work-life balance problem prioritising the worker preferences focusing on healthcare workers as a special case where personnel preferences are integrated into decision-making. The model has been comparatively solved with population-based algorithms for optimising weekly personnel schedules in order to make them more suitable for work-life balance. The population-based heuristic algorithms used for optimising the schedules are swarm intelligence algorithms; namely ant colony and particle swarm optimisation algorithms. The proposed approach allows the employees to opt their working hours and periods in the work-place, flexibly. We demonstrated with comparative analysis that the produced results with swarm intelligence algorithms evidently outperform one of the state-of-art works done with genetic algorithms, which proves the strength of the proposed problem solvers.
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 21, 2023 |
Online Publication Date | Dec 23, 2023 |
Publication Date | Jan 31, 2024 |
Deposit Date | Dec 22, 2023 |
Publicly Available Date | Jan 18, 2024 |
Journal | Computers and Industrial Engineering |
Print ISSN | 0360-8352 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 187 |
Article Number | 109857 |
DOI | https://doi.org/10.1016/j.cie.2023.109857 |
Public URL | https://uwe-repository.worktribe.com/output/11533996 |
Files
Heuristic and swarm intelligence algorithms for work-life balance problem
(1.2 Mb)
PDF
Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
You might also like
Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning
(2014)
Presentation / Conference Contribution
A multi-agent based approach for change management in manufacturing enterprises
(2013)
Journal Article
Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks
(2014)
Presentation / Conference Contribution
Stochastic model of TCP and UDP traffic in IEEE 802.11b/g
(2014)
Presentation / Conference Contribution
Cognitive access point to handle delay sensitive traffic in WLANs
(2015)
Presentation / Conference Contribution
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search