The basic theories, development and applications of particle swarm optimization and genetic algorithm are introducedd.Some models of improved PSO algorithms are outlined. Characteristics of PSO and GA are compared. Two methods of hybrid of PSO and GA at present was summarized:hybrid with two algorithms entirely or with only a few steps ,and illustrated with flowchart.Limitation of two methods o...

in this paper, the static var compensator (svc) has been used to improve dynamic behaviour of power system. to do this, a new objective function is formulated considering power loss reduction, voltage profile improvement and loadability margin decrease. other contribution of this research is proposing a novel structure for particle swarm optimization (pso) algorithm through modifying the initia...

In this paper a novel invisible robust watermarking scheme for embedding and extracting a digital watermark in an image is presented. The novelty lies in determining perceptually important coefficients of transform in the host image using simple Haar Wavelet Transform (HWT) and Genetic Algorithm(GA)-Particle Swarm Optimization(PSO) based hybrid optimization. Invisible watermark is embedded such...

The Probabilistic Traveling Salesman Problem (PTSP) is a variation of the well known Traveling Salesman Problem (TSP). This problem arises when the information about customers demand is not available at the moment of the tour generation and/or the tour re-calculating cost is too elevated. In this article, a Hybrid Algorithm combining Particle Swarm Optimization (PSO) and Simulated Annealing (SA...

in this paper, a combinational optimization algorithm is introduced to obtain the best size and location of static compensator (statcom) in power systems. its main contribution is considering contingency analysis where lines outages may lead to infeasible solutions especially at peak loads and it commonly can be vanished by load-shedding. the objective of the proposed algorithm is firstly to pr...

In simulation-based design optimization, one of the greatest challenges is the intensive computing burden. In order to reduce the computational time, a parallel implementation of the particle swarm optimization (PSO) algorithm on graphic processing unit (GPU) is presented in this paper. Instead of executed on the central processing unit (CPU) in a serial manner, the PSO algorithm is executed in...

According to researches, activation was a minor strategy of improving Particle Swarm Algorithm. For proofing the possibility of activation strategy could be a main strategy for improving Particle Swarm Algorithm, this article adopt the concept of mutation in Genetic Algorithm to improve Particle Swarm Optimization. The experimental results show three advantages for the activation strategies. Fi...

This survey focuses on the problem of parameters selection in image edge detection by ant colony optimization (ACO) algorithm. By introducing particle swarm optimization (PSO) algorithm to optimize parameters in ACO algorithm, the fitness function based on connectivity of image edge is proposed to evaluate the quality of parameters in ACO algorithm. And the ACO-PSO algorithm is applied to image...

In this paper, an improvement of the particle swarm optimization (PSO) algorithm is proposed. The aim of this algorithm is to iteratively resolve the cost problem of the Multivariable Generalized Predictive Control (MGPC) method under multiple constraints previously reduced. An ill-conditioned chemical process modelled by an uncertain Multi-Input & Multi-Output (MIMO) plant is controlled in ord...

global optimization methods play an important role to solve many real-world problems. flower pollination algorithm (fp) is a new nature-inspired algorithm, based on the characteristics of flowering plants. in this paper, a new hybrid optimization method called hybrid flower pollination algorithm (fppso) is proposed. the method combines the standard flower pollination algorithm (fp) with the par...