— Particle swarm optimization (PSO) is a stochastic global optimization algorithm inspired by social behavior of bird flocking in search for food, which is a simple but powerful...
Particle Swarm Optimization (PSO) has recently emerged as a nature inspired algorithm for real parameter optimization. This article describes a method for improving the final accur...
This work extends the Particle Swarm Optimization (PSO) algorithm for working on dynamic environments. We propose an evaporation mechanism to solve the outdated memory problem. We...
This paper presents a comparative study of three popular, Evolutionary Algorithms (EA); Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) ...
This study is concerned with the application of multi-objective particle swarm optimization (MOPSO) approaches to the framework of collaborative fuzzy clustering. In particular, t...
In image guided surgery, the registration of preand intra-operative image data is an important issue. In registrations, we seek an estimate of the transformation that registers th...
This paper describes a method for improving the final accuracy and the convergence speed of Particle Swarm Optimization (PSO) by adapting its inertia factor in the velocity updati...
— We investigate the use of Particle Swarm Optimization (PSO), and compare with Genetic Algorithms (GA), for a particular robot behavior-learning task: the training of an animat ...
The discrete particle swarm optimization (DPSO) is a kind of particle swarm optimization (PSO) algorithm to find optimal solutions for discrete problems. This paper proposes an i...
Two new variants of Particle Swarm Optimization (PSO) called AMPSO1 and AMPSO2 are proposed for global optimization problems. Both the algorithms use adaptive mutation using Beta ...