__________________________________________________________________________ A recently developed radii-based evolutionary algorithm designed to solve multimodal optimization problems is presented. The approach can be placed within the genetic chromodynamics framework. The basic motivation for modifying the original algorithm was to preserve its ability to search for many optima in parallel while...

In this paper, we propose a Hierarchical Particle Swarm Optimization (HPSO) algorithm model for multimodal function optimization. All particles will be classified into several groups, these groups operated at two levels: one level is to find location of global optima clusters with its particles; the other is to exactly distinguish multiple global optima in clusters. By this mechanism, algorithm...

This research paper presents a new evolutionary optimization model based on the particle swarm optimization (PSO) algorithm that incorporates the flocking behavior of a spider. The search space is divided into several segments like the net of a spider. The social information sharing among the swarms are made strong and adaptive. The main focus is on the fitness of the swarms adjusting to the le...

Particle Swarm Optimization (PSO) has shown good performance in many optimization problems. However, it easily falls into local optima and suffers from premature convergence on complex multimodal problems. To help trapped particles escape from local minima, a novel hybrid jumps strategy is proposed. The main idea of the new jump strategy is to monitor the changes of previous best particle and t...

The prediction of certain thermodynamic properties of pure substances and mixtures with calculation methods is a frequent task during the process design in chemical engineering. Group contribution models divide the molecules into functional groups and if the model parameters for theses groups are known, predictions of compounds that comprise these groups are possible. The model parameters have ...