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A particle swarm searching for the global minimum of a function. In computational science, particle swarm optimization (PSO) [1] is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.
Multi-swarm optimization is a variant of particle swarm optimization (PSO) based on the use of multiple sub-swarms instead of one (standard) swarm. The general approach in multi-swarm optimization is that each sub-swarm focuses on a specific region while a specific diversification method decides where and when to launch the sub-swarms.
Particle swarm optimization (PSO) is a global optimization algorithm for dealing with problems in which a best solution can be represented as a point or surface in an n-dimensional space. Hypotheses are plotted in this space and seeded with an initial velocity , as well as a communication channel between the particles.
James Kennedy (born November 5, 1950) is an American social psychologist, best known as an originator and researcher of particle swarm optimization.The first papers on the topic, by Kennedy and Russell C. Eberhart, were presented in 1995; since then tens of thousands of papers have been published on particle swarms.
Particle swarm optimization is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, dubbed particles , and moving these particles around in the search space according to simple ...
It can be shown that the limiting case corresponds to the standard Particle Swarm Optimization (PSO). In fact, if the inner loop (for j) is removed and the brightness I j {\displaystyle I_{j}} is replaced by the current global best g ∗ {\displaystyle g^{*}} , then FA essentially becomes the standard PSO.
Maurice Clerc worked in the Research and Development department of France Télécom.. His early work focused on fuzzy representations. [2] [3] [4] He was later recognized as a world specialist in particle swarm optimization (PSO) [5] [6] jointly with James Kennedy.
Particle swarm optimization is another algorithm widely used to solve problems related to swarms. It was developed in 1995 by Kennedy and Eberhart and was first aimed at simulating the social behaviour and choreography of bird flocks and fish schools.