A new hybrid approach to optimization in dynamical environments called Collaborative Evolutionary-Swarm Optimization (CESO) is presented. CESO tracks moving optima in a dynamical ...
Recent work has introduced a simulation model of ecological processes in terms of a very simple Particle Swarm algorithm. This abstract model produced qualitatively realistic beha...
Geometric particle swarm optimization (GPSO) is a recently introduced generalization of traditional particle swarm optimization (PSO) that applies to all combinatorial spaces. The...
Evolution strategy (ES) and particle swarm optimization (PSO) are two of the most popular research topics for tackling real-parameter optimization problems in evolutionary computa...
Several theoretical analyses of the dynamics of particle swarms have been offered in the literature over the last decade. Virtually all rely on substantial simplifications, incl...
As a part of many e-learning initiatives, a set of learning units must be arranged in a particular order to meet the learners’ requirements. This process is known as sequencing ...
— 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...
The multiobjective Quadratic Assignment Problem (mQAP) is considered as one of the hardest optimization problems but with many real-world applications. Since it may not be possibl...
— We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES...
This paper addresses the problem of reconstructing the 3D motion trajectories of particle swarms using two temporally synchronized and geometrically calibrated cameras. The 3D traj...