Estimation of distribution algorithm in continuous domains is generally based on assumption that variables subject to Gaussian distribution and that the probability model is single-peaked one

which is not capable of describing the solutions distribution effectively for complex optimization problems.Aiming to improve such drawback

an estimation of distribution algorithm depending upon sequential importance sampling particle filters is presented.In this algorithm

the variables are not required to subject to Gaussian distribution.Instead

the distribution of samples is represented by weighted particles and the used probability model is multi-peaked.The next generation of population is produced from the above distribution.The simulation results indicate the validity of the algorithm.