Comparison of particle swarm optimization and tabu search algorithms for portfolio selection problem

Using Metaheuristics models and Evolutionary Algorithms for solving portfolio problem has been considered in recent years.In this study, by using particles swarm optimization and tabu search algorithms we  optimized two-sided risk measures . A standard exact penalty function transforms the considered portfolio selection problem into an equivalent unconstrained minimization problem. And in finally the historical data from s&p100 from years 2007 through 2009 is used as model input and then  the model was solved  and  these algorithms were compared.