Particle swarm optimization (PSO) is a recently developed optimization method that has attracted interest of researchers in various areas. PSO has been shown to be effective in solving a variety of complex optimization problems. With properly chosen parameters, PSO can converge to local optima. However, conventional PSO does not have global convergence. Empirical evidences indicate that the PSO...

We have previously proposed a hybrid particle swarm optimisation/ant colony optimisation (PSO/ACO) algorithm for the discovery of classification rules. Unlike a conventional PSO algorithm, this hybrid algorithm can directly cope with nominal attributes, without converting nominal values into binary numbers in a preprocessing phase. PSO/ACO2 also directly deals with both continuous and nominal a...

Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. This paper proposes a Multi Swarm Particle Swarm Optimization (MS-PSO) algorithm inspired by the animal collective behavior, the movement of the swarm and the intelligence of the ...

Abstract— Particle Swarm Optimization (PSO) algorithm is swarm intelligence based algorithm which is used for solving optimization problem. PSO simulates the intelligent foraging behavior of a flock of birds. This paper presents a modification in PSO and develops an algorithm called Highly Convergent Particle Swarm Optimization (HCPSO) algorithm, in which the velocity of particle is made to be ...

In this paper we investigate the application of the Particle Swarm Optimization (PSO) technique for solving the Hardware/Software partitioning problem. The PSO is attractive for the Hardware/Software partitioning problem as it offers reasonable coverage of the design space together with O(n) main loop's execution time, where n is the number of proposed solutions that will evolve to provide the ...

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the...

1. First of all, this lecture presents research experience such as immune system, genetic algorithm, particle swarm optimization, bacterial foraging, and its hybrid system and application to real system. This lecture will also show research experience and results of emotion for emotion robot by AI. From research experience, immune system, PSO (Particle Swarm Optimization), BF (Bacteria Foraging...