Circuit Design Based on Particle Swarm Optimization Algorithms

Abstract

This work investigates the application of Particle Swarm Optimization (PSO) algorithms in the field of evolutionary electronics. PSO was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities. PSO achieves its optimum solution by starting from a group of random solution and then searching repeatedly. We propose the new means for designing electronic circuits and introduce the modified PSO algorithm. For the case studies this means has proved to be efficient, experiments show that we have better results.

Constrained Engineering Optimization Algorithm Based on Elite Selection

“…A cylindrical vessel is capped at both ends by hemispherical heads as shown in Figure 10. The objective is to minimize the total cost, including the cost of Using the same notation given by Coello [18], the problem can be stated as follows: (10) Subject to This problem has been solved before by Sandgren using a branch and bound technique [19], by Kannan and Kramer using an augmented Lagrangian Multiplier approach [20], by Deb and Gene using Genetic Adaptive Search [21], by Coello using GA-based co-evolution model [17] and a feasibility-based tournament selection scheme [15]. In this paper, the new algorithm is run 50 times independently.…”

“…A number of scientific achievements had emerged in these fields [5,6,7]. PSO was proved to be a sort of high efficient optimization algorithm by numerous research and experiments [8,9,10,11,12,13]. PSO is a meta-heuristic as it makes few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions.…”