Starkey, Andrew and Hagras, Hani and Shakya, Siddhartha and Owusu, Gilbert (2016) A Genetic Algorithm Based Approach for the Simultaneous Optimisation of Workforce Skill Sets and Team Allocation. In: Research and Development in Intelligent Systems XXXIII - Incorporating Applications and Innovations in Intelligent Systems XXIV. Proceedings of AI-2016, The Thirty-Sixth SGAI International Conference on Innovative Techniques and Applications of Artificial. Springer, 253 - 266. ISBN 978-3-319-47174-7. Official URL: https://doi.org/10.1007/978-3-319-47175-4
Starkey, Andrew and Hagras, Hani and Shakya, Siddhartha and Owusu, Gilbert (2016) A Genetic Algorithm Based Approach for the Simultaneous Optimisation of Workforce Skill Sets and Team Allocation. In: Research and Development in Intelligent Systems XXXIII - Incorporating Applications and Innovations in Intelligent Systems XXIV. Proceedings of AI-2016, The Thirty-Sixth SGAI International Conference on Innovative Techniques and Applications of Artificial. Springer, 253 - 266. ISBN 978-3-319-47174-7. Official URL: https://doi.org/10.1007/978-3-319-47175-4
Starkey, Andrew and Hagras, Hani and Shakya, Siddhartha and Owusu, Gilbert (2016) A Genetic Algorithm Based Approach for the Simultaneous Optimisation of Workforce Skill Sets and Team Allocation. In: Research and Development in Intelligent Systems XXXIII - Incorporating Applications and Innovations in Intelligent Systems XXIV. Proceedings of AI-2016, The Thirty-Sixth SGAI International Conference on Innovative Techniques and Applications of Artificial. Springer, 253 - 266. ISBN 978-3-319-47174-7. Official URL: https://doi.org/10.1007/978-3-319-47175-4
Abstract
Item Type: | Book Section |
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Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
Depositing User: | Hani Hagras |
Date Deposited: | 22 Dec 2016 16:13 |
Last Modified: | 09 Nov 2021 16:28 |
URI: | http://repository.essex.ac.uk/id/eprint/18640 |
Available files
Filename: BCS-AI2016_Final.pdf