Genetic Programming and Evolvable Machines
Hybrid meta-heuristics algorithms for task assignment in heterogeneous computing systems
Computers and Operations Research
On the application of linear transformations for genetic algorithms optimization
International Journal of Knowledge-based and Intelligent Engineering Systems
A simulated annealing approach to speaker segmentation in audio databases
Engineering Applications of Artificial Intelligence
Binary Optimization: On the Probability of a Local Minimum Detection in Random Search
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Minimizing interference in satellite communications using transiently chaotic neural networks
Computers & Mathematics with Applications
Application of two Hopfield neural networks for automatic four-element LED inspection
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hybrid meta-heuristics algorithms for task assignment in heterogeneous computing systems
Computers and Operations Research
Wireless Personal Communications: An International Journal
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Hybrid cross-entropy method/Hopfield neural network for combinatorial optimization problems
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
ICNC'09 Proceedings of the 5th international conference on Natural computation
ICNC'09 Proceedings of the 5th international conference on Natural computation
Frequency assignment problem in satellite communications using differential evolution
Computers and Operations Research
Expert Systems with Applications: An International Journal
Simulated annealing algorithm with adaptive neighborhood
Applied Soft Computing
Engineering Applications of Artificial Intelligence
Hi-index | 0.00 |
A hybrid Hopfield network-simulated annealing algorithm (HopSA) is presented for the frequency assignment problem (FAP) in satellite communications. The goal of this NP-complete problem is minimizing the cochannel interference between satellite communication systems by rearranging the frequency assignment, for the systems can accommodate the increasing demands. The HopSA algorithm consists of a fast digital Hopfield neural network which manages the problem constraints hybridized with a simulated annealing which improves the quality of the solutions obtained. We analyze the problem and its formulation, describing and discussing the HopSA algorithm and solving a set of benchmark problems. The results obtained are compared with other existing approaches in order to show the performance of the HopSA approach.