The correlation-triggered adaptive variance scaling IDEA
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Clustering and learning Gaussian distribution for continuous optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This article presents a robust EDA for global optimization with real parameters. The approach is based on the linear combination of individuals of two populations. One is the current population Pt, from which a probability density model is created and a new population Ps is simulated. The new population Pt+1 is a linear combination of Pt and Ps. The linear combination factor involved is self-adaptive.