The Ant Colony Metaphor for Searching Continuous Design Spaces
Selected Papers from AISB Workshop on Evolutionary Computing
Continuous interacting ant colony algorithm based on dense heterarchy
Future Generation Computer Systems - Special issue: Computational chemistry and molecular dynamics
GPU-based parallel particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
MAX-MIN Ant System on GPU with CUDA
ICICIC '09 Proceedings of the 2009 Fourth International Conference on Innovative Computing, Information and Control
Parallel ant colony for nonlinear function optimization with graphics hardware acceleration
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Computation of Capacity Benefit Margin using Differential Evolution
International Journal of Computing Science and Mathematics
Evaluation of parallel particle swarm optimization algorithms within the CUDATM architecture
Information Sciences: an International Journal
A survey on parallel ant colony optimization
Applied Soft Computing
Parallelization Strategies for Ant Colony Optimisation on GPUs
IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
International Journal of Computing Science and Mathematics
An improved particle swarm optimisation for solving generalised travelling salesman problem
International Journal of Computing Science and Mathematics
| Hi-index | 0.00 |
A novel parallel approach to run continuous ant colony optimisation CACO algorithm on graphic processing unit GPU is presented in this paper for solving large scale continuous optimisation problem. CACO which is an extension to continuous domains from standard ACO is a kind of population-based meta-heuristics in essence. The mechanism of algorithm is described in detail. Its parallel implementation on compute unified device architecture CUDA is proposed in our work. The experiment results on actual hardware to optimise many-dimensions test functions are given. The results and analyses show the excellent performance of algorithm.