Outputs (21)

Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra (2024)
Journal Article
Kok, Y. E., Crisford, A., Parkes, A., Venkateswaran, S., Oreffo, R., Mahajan, S., & Pound, M. (2024). Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra. Scientific Reports, 14(1), Article 15902. https://doi.org/10.1038/s41598-024-66857-6

Raman spectroscopy is a rapid method for analysing the molecular composition of biological material. However, noise contamination in the spectral data necessitates careful pre-processing prior to analysis. Here we propose an end-to-end Convolutional... Read More about Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.

Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies (2023)
Journal Article
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Jaouen, L., & Bécot, F.-X. (2023). Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies. Journal of the Acoustical Society of America, 153(5), Article 2945. https://doi.org/10.1121/10.0019455

When designing passive sound-attenuation structures, one of the challenging problems that arise is optimally distributing acoustic porous materials within a design region so as to maximise sound absorption while minimising material usage. To identify... Read More about Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies.

Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials (2021)
Journal Article
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Sreekumar, A., Jaouen, L., & Bécot, F. (2021). Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials. Journal of the Acoustical Society of America, 150(4), 3164-3175. https://doi.org/10.1121/10.0006784

When designing sound packages, often fully filling the available space with acoustic materials is not the most absorbing solution. Better solutions can be obtained by creating cavities of air pockets, but determining the most optimal shape and topolo... Read More about Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials.

A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices (2019)
Journal Article
Cui, T., Bai, R., Ding, S., Parkes, A. J., Qu, R., He, F., & Li, J. (2020). A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices. Soft Computing, 24, 2809–2831. https://doi.org/10.1007/s00500-019-04517-y

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Portfolio optimization is one of the most important problems in the finance field. The traditional Markowitz mean-variance model is often unrealistic since it relies on the perfect market... Read More about A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices.

Pattern-Based Approach to the Workflow Satisfiability Problem with User-Independent Constraints (2019)
Journal Article
Karapetyan, D., J. Parkes, A., Gutin, G., & Gagarin, A. (2019). Pattern-Based Approach to the Workflow Satisfiability Problem with User-Independent Constraints. Journal of Artificial Intelligence Research, 66, 85-122. https://doi.org/10.1613/jair.1.11339

The fixed parameter tractable (FPT) approach is a powerful tool in tackling computationally hard problems. In this paper, we link FPT results to classic artificial intelligence (AI) techniques to show how they complement each other. Specifically, we... Read More about Pattern-Based Approach to the Workflow Satisfiability Problem with User-Independent Constraints.

Learning the Quality of Dispatch Heuristics Generated by Automated Programming (2018)
Book Chapter
Parkes, A. J., Beglou, N., & Ozcan, E. (2019). Learning the Quality of Dispatch Heuristics Generated by Automated Programming. In Learning and Intelligent Optimization (154-158). Springer Verlag. https://doi.org/10.1007/978-3-030-05348-2_13

One of the challenges within the area of optimisation, and AI in general, is to be able to support the automated creation of the heuristics that are often needed within effective algorithms. Such an example of automated programming may be performed b... Read More about Learning the Quality of Dispatch Heuristics Generated by Automated Programming.

Exploring the landscape of the space of heuristics for local search in SAT (2017)
Presentation / Conference Contribution
Burnett, A. W., & Parkes, A. J. (2017). Exploring the landscape of the space of heuristics for local search in SAT.

Local search is a powerful technique on many combinatorial optimisation problems. However, the effectiveness of local search methods will often depend strongly on the details of the heuristics used within them. There are many potential heuristics, an... Read More about Exploring the landscape of the space of heuristics for local search in SAT.

International Portfolio Optimisation with Integrated Currency Overlay Costs and Constraints (2017)
Journal Article
Chatsanga, N., & Parkes, A. J. (2017). International Portfolio Optimisation with Integrated Currency Overlay Costs and Constraints. Expert Systems with Applications, 83, 333-349. https://doi.org/10.1016/j.eswa.2017.04.009

International financial portfolios can be exposed to substantial risk from variations of the exchange rates between the countries in which they hold investments. Nonetheless, foreign exchange can both generate extra return as well as loss to a portfo... Read More about International Portfolio Optimisation with Integrated Currency Overlay Costs and Constraints.

Fairness in examination timetabling: student preferences and extended formulations (2017)
Journal Article
Muklason, A., Parkes, A. J., Özcan, E., McCollum, B., & McMullan, P. (2017). Fairness in examination timetabling: student preferences and extended formulations. Applied Soft Computing, 55, 302-318. https://doi.org/10.1016/j.asoc.2017.01.026

Variations of the examination timetabling problem have been investigated by the research community for more than two decades. The common characteristic between all problems is the fact that the definitions and data sets used all originate from actual... Read More about Fairness in examination timetabling: student preferences and extended formulations.

Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem (2017)
Journal Article
Karapetyan, D., Punnen, A., & Parkes, A. J. (2017). Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem. European Journal of Operational Research, 260(2), 494-506. https://doi.org/10.1016/j.ejor.2017.01.001

We study the Bipartite Boolean Quadratic Programming Problem (BBQP) which is an extension of the well known Boolean Quadratic Programming Problem (BQP). Applications of the BBQP include mining discrete patterns from binary data, approximating matrice... Read More about Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem.