Solving Non Linear Function with Two Variables by Using Particle Swarm Optimization Algorithm

Abstract

The meaning of the Particle Swarm Optimization (PSO) refers to a relativelynew family of algorithms that may be used to find optimal (or near optimal)solutions to numerical and qualitative problems.The genetic algorithm (GA) is an adaptive search method that has the ability for asmart search to find the best solution and to reduce the number of trials and timerequired for obtaining the optimal solution.The aim of this paper is to use the PSO to solve some kinds of two variables functionwhich submits to optimize function filed. We investigate a comparison study betweenPSO and GA to this kind of problems. The experimental results reported will shedmore light into which algorithm is best in solving optimization problems.The work shows the iteration results obtained with implementation in Delphiversion 6.0 visual programming language exploiting the object oriented tools ofthis language.