the gravitational search algorithm (gsa) is a novel optimization methodbased on the law of gravity and mass interactions. it has good ability to search forthe global optimum, but its searching speed is really slow in the last iterations. sothe hybridization of particle swarm optimization (pso) and gsa can resolve theaforementioned problem. in this paper, a modified pso, which the movement ofpar...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

Particle swarm optimization (PSO) is a population-based stochastic optimization that has been widely applied to a variety of problems. However, it is easily trapped into the local optima and appears premature convergence during the search process. To address these problems, we propose a new particle swarm optimization by introducing chaotic maps (tent map and logistic map) and Gaussian mutation...

This study aimed at the implementation and synchronization control of cardiac circuit. First, the MATLAB-Simulink was used to simulate the dynamic behavior of cardiac chaotic circuit, and simple electronic modules were used to implement the cardiac system. Then the Particle Swarm Optimization PSO was used to seek for the proportional, integral, and derivative gains of optimal PID controller, an...

In order to overcome the premature convergence in the particle swarm optimization algorithm, dynamically chaotic perturbation is introduced to form a dynamically chaotic PSO, briefly denoted as DCPSO. To get rid of the drawbacks of simply finding the convex cluster and being sensitive to the initial partitions in k -means algorithm, a novel hybrid clustering algorithm combined with the DCPSO is...

In this paper, we incorporate pheromone courtship mode of biology to improve particle swarm optimizer. The particle swarm optimization technique has ever since turned out to be a competitor in the field of numerical optimization. A particle swarm optimization consists of a number of individuals refining their knowledge of the given search space. Particle swarm optimizations are inspired by part...

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of...