Novel Swarm Intelligence Algorithms: Application to Bioinformatics and System Biology
Funder
Royal Society, UK, and National Science Foundations, China
Value
£12,000 for Coventry University; £12,000 for Jiangnan University, China
Collaborators
Dr. Jun Sun, Dr. Wei Fang, Prof. Xiaojun Wu from Jiangnan University, China
Project objectives
- To design two novel swarm intelligence algorithms, i.e. a so-called social optimization (SO) algorithm and a random drift particle swarm optimization (RDPSO) algorithm, as well as their binary versions for solving discrete optimization problems.
- To address the theoretical foundations of these algorithms, including convergence and convergence rate of these algorithms, the time complexity, the relationship between the convergence rate and time complexity, and the performance stability of these algorithms.
- To apply the SO and the RDPSO algorithms to Bioinformatics and System Biology problems, such as feature selection for gene expression data and the modeling and optimization of biochemical metabolic networks.
Research impact
The outcome of this project will help promote the development of the field of computational intelligence and applications in the UK, in particular the theoretical foundations of swarm intelligence and evolutionary computation. Researchers in computational intelligence will directly benefit by new optimization methods developed by this project validated in the context of challenging applications. This project will help maintain and extend the links between the UK researchers and Chinese researchers, which will increase the international impact of UK and Chinese researchers as a result.
