An Analysis of the Operation Factors of Three PSO-GA-ED Meta-Heuristic Search Methods for Solving a Single-Objective Optimization Problem.

In this study, we evaluate several nongradient (evolutionary) search strategies for minimizing mathematical function expressions. We developed and tested the genetic algorithms, particle swarm optimization, and differential evolution in order to assess their general efficacy in optimization of mathematical equations. A comparison is then made between the results and the efficiency, which is determined by the number of iterations, the observed accuracy, and the overall run time.