Title :
Use of intelligent-particle swarm optimization in electromagnetics
Author :
Ciuprina, Gabriela ; Ioan, Daniel ; Munteanu, Irina
Author_Institution :
Numerical Methods Lab., Univ. of Bucharest, Romania
fDate :
3/1/2002 12:00:00 AM
Abstract :
The paper describes a new stochastic heuristic algorithm for global optimization. The new optimization algorithm, called intelligent-particle swarm optimization (IPSO), offers more intelligence to particles by using concepts such as: group experiences, unpleasant memories (tabu to be avoided), local landscape models based on virtual neighbors, and memetic replication of successful behavior parameters. The new individual complexity is amplified at the group level and consequently generates a more efficient optimization procedure. A simplified version of the IPSO algorithm was implemented and compared with the classical PSO algorithm for a simple test function and for the Loney´s solenoid
Keywords :
computational complexity; electromagnetic field theory; electronic engineering computing; heuristic programming; optimisation; solenoids; stochastic processes; IPSO; IPSO algorithm; Loney´s solenoid; PSO algorithm; complexity; efficient optimization procedure; electromagnetics; global optimization; group experiences; group level complexity; intelligent-particle swarm optimization; local landscape models; memetic replication; particle intelligence; stochastic heuristic algorithm; successful behavior parameters; test function; unpleasant memories; virtual neighbors; Birds; Concrete; Electromagnetic fields; Heuristic algorithms; Optimization methods; Parallel algorithms; Particle swarm optimization; Solenoids; Stochastic processes; Testing;
Journal_Title :
Magnetics, IEEE Transactions on
