A Gaussian correction scheme is proposed and a G-PSO algorithm is proposed. Through the introduction of Gaussian coefficients, we modify the fitness function of PSO algorithm, the particle individual velocity and the position updating strategy. Furthermore, two test functions are used to analyze the performance of G-PSO algorithm to solve the global optimal solution. Experimental results of vir...

In this paper, five previous Particle Swarm Optimization (PSO) algorithms for multimodal function optimization are reviewed. A new and a successful PSO based algorithm, named as CPSO is proposed. CPSO enhances the exploration and exploitation capabilities of PSO by performing search using a random walk and a hill climbing components. Furthermore, one of the previous PSO approaches is improved i...

In the paper a modified particle swarm optimization (MPSO) is proposed where concepts from firefly algorithm (FA) are borrowed to enhance the performance of particle swarm optimization (PSO). The modifications focus on the velocity vectors of the PSO, which fully use beneficial information of the position of particles and increase randomization item in the PSO. Finally, the performance of the p...

Vigenere cipher is a polyalphabetic substitution cipher with a very large key space. In this paper we have investigated the use of PSO for the cryptanalysis of vigenere cipher and proposed PSO with Markov chain random walk in which some of the worst particles are replaced with new better random particles to enhance the efficiency of PSO algorithm. Based on our experimental results, it is shown ...

Many optimization problems in real world are dynamic in the sense that the global optimum value and the shape of fitness function may change with time. The task for the optimization algorithm in these environments is to find global optima quickly after the change in environment is detected. In this paper, we propose a new hybrid model of particle swarm optimization and cellular automata which a...

NNPC has been used widely to control nonlinear systems. However traditional gradient decent algorithm (GDA) needs a large computational cost, so that NNPC is not acceptable for systems with rapid dynamics. To apply NNPC in fast control of mobile robots, the paper proposes an improved optimization technique, particle swarm optimization with controllable random exploration velocity (PSO-CREV), to...

This paper introduces the Particle Swarm Optimization (PSO) algorithm to solve the optimal network reconfiguration problem for power loss reduction. The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems. It is a population-based approach. The PSO was inspired from natural behavior of the bees on how they find the location of most flowers. The p...

This paper presents a modification of tlte panicle swarm optimization algorithm (PSO) intended to combat the problem ofpremature convergence observed in many applications of PSO. The proposed new algorithm moves particles towards neorby particles of higher fitness, instead of amacting each panicle towards just the best position discovered so far by any particle. This is accomplished by using th...