This project aims to develop a generic, automated and robust search framework in support of the fibre network design.
To minimise the capital expenditure of fibre network planning, various search strategies are utilised, including multi- and single-point approaches, such as:
- Population-based Algorithms
- Genetic Algorithms
- Memetic Algorithms
- Single-point Search Algorithms
- Simulated Annealing-based Hyper-heuristics
- Sequence-based Hyper-heuristics
As this is a real-world problem, this project tries to build a framework to find the most cost-efficient network design utilising aforementioned algorithms that consider real-world (physical) constraints.
This research has been funded by the UK EPSRC (Engineering and Physical Sciences Research Council, grant number EP/S513696/1), with contributions from British Telecom in response to growing concerns over rising demand on fibre networks.
Related Program Codes
Representative Publications
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Arpaci, A., Chen, J., Drake, J. and Glover, T., 2021, December. Intelligent strategies to combine move heuristics in selection hyper-heuristics for real-world fibre network design optimisation. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 01-08). IEEE.
24-01-2022
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Arpaci, A., Chen, J., Drake, J.H. and Glover, T., 2022, July. Sequence-based Selection Hyper-heuristics for Real-World Fibre Network Design Optimisation. In 2022 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE.
06-09-2022
