Punctuated equilibria: a parallel genetic algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Fine-Grained Parallel Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Serial and Parallel Genetic Algorithms as Function Optimizers
Proceedings of the 5th International Conference on Genetic Algorithms
An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Power laws and the AS-level internet topology
IEEE/ACM Transactions on Networking (TON)
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Takeover time curves in random and small-world structured populations
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
The exploration/exploitation tradeoff in dynamic cellular genetic algorithms
IEEE Transactions on Evolutionary Computation
Using pair approximations to predict takeover dynamics in spatially structured populations
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Pair approximations of takeover dynamics in regular population structures
Evolutionary Computation
MODM: multi-objective diffusion model for dynamic social networks using evolutionary algorithm
The Journal of Supercomputing
Hi-index | 0.00 |
The application of network analysis to emergent mating topologies in spatially structured genetic algorithms is presented in this preliminary study as a framework for inferring evolutionary dynamics in recombinant evolutionary search. Emergent mating topologies of populations evolving on regular, scale-free, and small-world imposed spatial topologies are analyzed. When the population evolves on a scale-free imposed spatial topology, the topology of mating interactions is also found to be scale-free. However, due to the random initial placement of individuals in the spatial topology, the scale-free mating topology lacks correlation between fitness and vertex connectivity, resulting in highly variable convergence rates. Scale-free mating topologies are also shown to emerge on regular imposed spatial topologies under high selection pressure. Since these scale-free emergent mating topologies self-organize such that the most-fit individuals are inherently located in highly connected vertices, such emergent mating topologies are shown to promote rapid convergence on the test problem considered herein. The emergent mating topologies of populations evolving on small-world imposed spatial topologies are not found to possess scale-free or small-world characteristics. However, due to the decrease in the characteristic path length of the emergent mating topology, the rate of population convergence is shown to increase as the imposed spatial topology is tuned from regular to small-world.