Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
An Efficient Migration Scheme for Subpopulation-Based Asynchronously Parallel Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Forking Genetic Algorithm with Blocking and Shrinking Modes (fGA)
Proceedings of the 5th International Conference on Genetic Algorithms
Distributed cell biology simulations with e-cell system
LSGRID'04 Proceedings of the First international conference on Life Science Grid
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Island Parallel GA divides a population into subpopulations and assigns them to processing elements on a parallel computer. Then each subpopulation searches the optimal solution independently, and exchanges individuals periodically. This exchange operation is called migration. In this research, we propose a new algorithm that migrants are exchanged asynchronously among multiform subpopulations which have different search conditions. The effect of our algorithm on combinational optimization problems was verified by applying the algorithm to Knapsack Problem and Royal Road Functions using parallel computer CRAY-T3E. We obtained the results that our algorithm maintained the population's diversity effectively and searches building blocks efficiently.