Multi-miminum Particle Swarm Optimization
To overcome the shortcoming that the standard Particle Swarm Optimization(PSO) only can find a minimum of the objective function,we propose an improved PSO which not only can find all the minimums of the objective function,but also has a strong global convergence.In each generation,through searching the extreme particles in the population,we can get the extreme-point information of the objective function and achieve the purpose of searching more than one minimum of the objective function.In the standard Particle Swarm Optimization,when searching the minimum of the multiple-minimum function,the global best particle may vibrate between different minimums,our algorithm conquers this defect and improves the convergence and accuracy.The tests of some typical one-dimensional,two-dimensional and multi-dimensional objective functions show the improved PSO is effective.