Particle swarm optimization algorithm based on markov model and its stochastic process analysis
Qiu Chen · Computer Engineering and Applications Journal · 2009
Inspired by the theoretic analysis of genetic algorithm based on markov process,a new form of particle swarm optimization algorithm is advanced,which is convenient for analysis by the theory of markov process.The particle of new algorithm only memorizes the information of swarm in finite steps,and forgets the old information.Then the markov process model is established.The simulations of functions optimization show that the new algorithm has good ability to find the global solution,and the homogeneous markov process is got from the new algorithm.