A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO) algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for m...

in this paper we introduce an improvement in the path planning algorithm for the humanoid soccer playing robot which uses ferguson splines and pso (particle swarm optimization). the objective of the algorithm is to find a path through other playing robots to the ball, which should be as short as possible and also safe enough. ferguson splines create preliminary paths using random generated para...

In this paper, optimization of the backstepping controller parameters in a grid-connected single-phase inverter is studied using Imperialist competitive algorithm (ICA), Genetic Algorithm (GA) and Particle swarm optimization (PSO) algorithm. The controller is developed for the system based on state-space averaged model. By selection of a suitable Lyapunov function, stability of the proposed con...

Vehicle routing problem is a NP-hard problem in combination optimization problem, It is influenced by many factors, and the process is complex. However, the search space of particle swarm algorithm is limited and prone to precocious phenomenon. In this paper, we based on the original particle swarm optimization, present a new way of location update algorithm (VPSO).VPSO in the process of solvin...

This paper proposes a novel population-based evolution algorithm named grouping-shuffling particle swarm optimization (GSPSO) by hybridizing particle swarm optimization (PSO) and shuffled frog leaping algorithm (SFLA) for continuous optimization problems. In the proposed algorithm, each particle automatically and periodically executes grouping and shuffling operations in its flight learning evo...

A Multi-objective problems occurs wherever optimal solution necessary to be taken in the presence of tradeoffs between more than one conflicting objectives. Usually the population’s values of MOPSO algorithm are random which leads to random search quality. Particle Swarm Optimization Based on Multi Objective Functions with Uniform Design (MOPSO-UD), is proposed to enhance the accuracy of the pa...

The paper proposed a network scheduling in cloud computing based on intelligence Particle Swarm Optimization algorithm aimed at the disadvantages of cloud computing network scheduling. Firstly, on the basis of cloud model, used intelligence Particle Swarm Optimization algorithm with strong ability of global searching to find the better solution of cloud computing network scheduling then turned ...

Using Particle Swarm Optimization to handle complex functions with high-dimension it has the problems of low convergence speed and sensitivity to local convergence. The convergence of particle swarm algorithm is studied, and the condition for the convergence of particle swarm algorithm is given. Results of numerical tests show the efficiency of the results. Base on the idea of specialization an...