— Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution...
A new hybrid approach to optimization in dynamical environments called Collaborative Evolutionary-Swarm Optimization (CESO) is presented. CESO tracks moving optima in a dynamical ...
—As more and more real-world optimization problems become increasingly complex, algorithms with more capable optimizations are also increasing in demand. For solving large scale ...
Charged particle swarm optimization (CPSO) is well suited to the dynamic search problem since inter-particle repulsion maintains population diversity and good tracking can be achie...
Two new variants of Particle Swarm Optimization (PSO) called AMPSO1 and AMPSO2 are proposed for global optimization problems. Both the algorithms use adaptive mutation using Beta ...