Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Particle swarm with speciation and adaptation in a dynamic environment
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary Computation in Dynamic and Uncertain Environments (Studies in Computational Intelligence)
B-Cell Algorithm as a Parallel Approach to Optimization of Moving Peaks Benchmark Tasks
CISIM '07 Proceedings of the 6th International Conference on Computer Information Systems and Industrial Management Applications
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Multiswarms, exclusion, and anti-convergence in dynamic environments
IEEE Transactions on Evolutionary Computation
Adaptive Non-uniform Distribution of Quantum Particles in mQSO
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Properties of Quantum Particles in Multi-Swarms for Dynamic Optimization
Fundamenta Informaticae
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This paper presents research considering mixed multi-swarm optimization approach applied to dynamic environments. One of the versions of this approach, called mQSO is a subject of our special interest. The mQSO algorithm works with a set of particles divided into sub-swarms where every sub-swarm consists of two types of particles: classic and quantum ones. The research is focused on studying properties of the latter type. Two new distributions of new locations for the quantum particles are proposed: static and adaptive one. Both of them are based on an ï戮驴-stable symmetric distribution. In opposite to already published methods of distribution of new locations the proposed methods allow the locations to be distributed over the entire search space. Obtained results show high efficiency of the mQSO approach equipped with the proposed two new methods.