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13 results

Use of machine learning techniques to model wind damage to forests

Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...

Genetic Programming.

Conference Proceeding
Machado, P., Heywood, M. I., McDermott, J., Castelli, M., García-Sánchez, P., Burelli, P., …Sim, K. (2014)
Genetic Programming. In Genetic Programmingdoi:10.1007/978-3-319-16501-1
The 18th European Conference on Genetic Programming (EuroGP) took place during April 8–10, 2015. Copenhagen, Denmark was the setting, and the Nationalmuseet was the venue. Eur...

A Lifelong Learning Hyper-heuristic Method for Bin Packing.

Journal Article
Hart, E., Sim, K., & Paechter, B. (2015)
A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121
We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics ...

A hyper-heuristic ensemble method for static job-shop scheduling.

Journal Article
Hart, E., & Sim, K. (2016)
A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conq...

A real-world employee scheduling and routing application.

Conference Proceeding
Hart, E., Sim, K., & Urquhart, N. B. (2014)
A real-world employee scheduling and routing application. In C. Igel (Ed.), GECCO 2014 Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation, (1239-1242). https://doi.org/10.1145/2598394.2605447
We describe a hyper-heuristic application developed for a client to find quick, acceptable solutions to Workforce Schedul- ing and Routing problems. An interactive fitness fun...

Generating single and multiple cooperative heuristics for the one dimensional bin packing problem using a single node genetic programming island model.

Conference Proceeding
Sim, K., & Hart, E. (2013)
Generating single and multiple cooperative heuristics for the one dimensional bin packing problem using a single node genetic programming island model. In E. Alba (Ed.), Proceedgs of GECCO 2013, (1549-1556). https://doi.org/10.1145/2463372.2463555
Novel deterministic heuristics are generated using Single Node Genetic Programming for application to the One Dimensional Bin Packing Problem. First a single deterministic heu...

An improved immune inspired hyper-heuristic for combinatorial optimisation problems.

Conference Proceeding
Sim, K., & Hart, E. (2014)
An improved immune inspired hyper-heuristic for combinatorial optimisation problems. In C. Igel (Ed.), Proceedings of GECCO 2014 (Genetic and Evolutionary Computation Conference), (121-128). https://doi.org/10.1145/2576768.2598241
The meta-dynamics of an immune-inspired optimisation sys- tem NELLI are considered. NELLI has previously shown to exhibit good performance when applied to a large set of optim...

On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system.

Conference Proceeding
Hart, E., & Sim, K. (2014)
On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system. In Proceedings of PPSN, 13th International Conference on Parallel problem Solving from Nature, (282-291). https://doi.org/10.1007/978-3-319-10762-2_28
Real-world applications of optimisation techniques place more importance on finding approaches that result in acceptable quality solutions in a short time-frame and can provid...

Learning to solve bin packing problems with an immune inspired hyper-heuristic.

Conference Proceeding
Sim, K., Hart, E., & Paechter, B. (2013)
Learning to solve bin packing problems with an immune inspired hyper-heuristic. In P. Liò, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life, ECAL 2013, 856-863. https://doi.org/10.7551/978-0-262-31709-2-ch126
Motivated by the natural immune system's ability to defend the body by generating and maintaining a repertoire of antibodies that collectively cover the potential pathogen spa...

Novel Hyper-heuristics Applied to the Domain of Bin Packing

Thesis
Sim, K. Novel Hyper-heuristics Applied to the Domain of Bin Packing. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/id/eprint/7563
Principal to the ideology behind hyper-heuristic research is the desire to increase the level of generality of heuristic procedures so that they can be easily applied to a wid...