Co-evolving parasites improve simulated evolution as an optimization procedure
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Journal of Global Optimization
Methods for Competitive Co-Evolution: Finding Opponents Worth Beating
Proceedings of the 6th International Conference on Genetic Algorithms
Parallel and Distributed Computing with Coevolutionary Algorithms
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Co-evolutionary particle swarm optimization to solve min-max problems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Particle swarm optimization for integer programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An Efficient Fine-grained Parallel Genetic Algorithm Based on GPU-Accelerated
NPC '07 Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops
New methods for competitive coevolution
Evolutionary Computation
Algorithmic performance studies on graphics processing units
Journal of Parallel and Distributed Computing
A performance study of general-purpose applications on graphics processors using CUDA
Journal of Parallel and Distributed Computing
A memetic approach to the automatic design of high-performance analog integrated circuits
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Evolutionary algorithms for minimax problems in robust design
IEEE Transactions on Evolutionary Computation
GPU-based parallel particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Swarm's flight: accelerating the particles using C-CUDA
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A Parallel Immune Algorithm Based on Fine-Grained Model with GPU-Acceleration
ICICIC '09 Proceedings of the 2009 Fourth International Conference on Innovative Computing, Information and Control
Coevolutionary augmented Lagrangian methods for constrainedoptimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An improved CUDA-based implementation of differential evolution on GPU
Proceedings of the 14th annual conference on Genetic and evolutionary computation
| Hi-index | 12.05 |
Several areas of knowledge are being benefited with the reduction of the computing time by using the technology of graphics processing units (GPU) and the compute unified device architecture (CUDA) platform. In case of evolutionary algorithms, which are inherently parallel, this technology may be advantageous for running experiments demanding high computing time. In this paper, we provide an implementation of a co-evolutionary differential evolution (DE) algorithm in C-CUDA for solving min-max problems. The algorithm was tested on a suite of well-known benchmark optimization problems and the computing time has been compared with the same algorithm implemented in C. Results demonstrate that the computing time can significantly be reduced and scalability is improved using C-CUDA. As far as we know, this is the first implementation of a co-evolutionary DE algorithm in C-CUDA.