implementation of particle swarm algorithm in optimization approach using simulation

optimization through simulation is considered anefficient tool in dealing with optimization problems. it’s a tool that iscapable to cover real world problems to a much more complete way than the otheroptimization tools. the problem of this tool is the necessity of heavyprocessing computations. this problem is caused not only since the simulationprocess is time consuming, but the objective function value at a point of thesolution space is required to simulate multiple performances. meta-models areapproaches to deal with this dilemma and have other problems that limit theiruse. meta-model remodel the simulation model; it reduces the complexity of themodel and yet the model still further away from the real world in this paper,the particle swarm optimization is modified so that can addition to remove themeta-models, reduce time to achieve optimal response.