By Topic

Boundary Conditions in Particle Swarm Optimization Revisited

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Shenheng Xu ; Dept. of Electr. Eng., California Univ., Los Angeles, CA ; Rahmat-Samii, Y.

In order to enforce particles to search inside the solution space of interest during the optimization procedure, various boundary conditions are currently used in particle swarm optimization (PSO) algorithms. The performances, however, vary considerably with the dimensionality of the problem and the location of the global optimum in the solution space. In this paper, different boundary conditions are categorized into two groups, namely, restricted and unrestricted, according to whether the errant particles are relocated inside the allowable solution space or not. Moreover, efforts are made to explore different hybrid unrestricted boundary conditions by introducing the favorable characteristics of the reflecting and damping boundary conditions into the existing invisible boundary condition. The performances of the boundary conditions are tested based on both mathematical benchmark functions and a real-world electromagnetic problem: the optimization of a 2-D 16-element array antenna. Simulation results are examined from both the effectiveness and efficiency of the algorithm. Comparisons show that the unrestricted boundary conditions are more efficient when the global optimum is inside the boundary of the solution space, and the damping boundary condition is more robust and consistent when the global optimum is close to the boundary

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:55 ,  Issue: 3 )