Evaluation of an improved Particle Swarm Optimization algorithm on MATLAB
Talha Ahmed Taj, Talha Ali Khan, Muhammad Kamran Asif, Imran Ijaz · 2013
An improved Particle Swarm Optimization(IPSO) algorithm is proposed in this paper. In the algorithm instead of using inertial weight and the particles velocity, two new factors are introduced, gamma which changes itself with respect to the number of iteration currently in progress. Gamma has a certain range which is a function of iteration; in our case it ranges from 0.94 to 0. A premature estimate mechanism is implemented so that after every iteration a new value of the gamma changes itself. Here the concept of the occurrence probability is also introduced and its values is set as 0.05. The benchmarks we used to check the algorithm are Sphere, Ackley, Rosenbrock, Schewfel's 2.26 and Rastrigin.