Solving Systems of Nonlinear Equations Using Quantum-behaved Particle Swarm Optimization
Sun Jun · Jisuanji yingyong yanjiu · 2007
Quantum-behaved particle swarm optimization was used to solve systems of nonlinear equations.When solving systems of nonlinear equations,the goal is to find an optimal solution for a fitness function.If there are multiple solutions,the fitness function is a multi-peaks function with multiple optima.So the notion of species was introduced.By using this method,the swarm population was divided into paralleled species subpopulations based on their similarity.Each species was grouped around a dominating particle called the species seed.Over successive iterations,species are able to simultaneously optimize towards multiple optima,so each solutions is ensure to be searched equally.The experiments demonstrate that the new algorithm to be successful in locating multiple solutions and better accuracy.