چکیده (انگلیسی):

This research aims to evaluate the optimum portfolio selection using with particle swarm algorithm. For this
purpose, the financial information of companies listed on the Iran stock exchange, during years 2007 to 2012 is collected
and using heuristic particle swarm algorithm and based on Markowitz model, mean-variance model and client risk
model, generating optimal portfolio from the stocks has been investigated. In total, the results of this study showed that
use of this algorithm can provide solutions both close together and close to optimality, and causes confidence of the
investors' investment for making decisions. Also, based on the response obtained by performing several experiments it
can be claimed that in Markowitz and mean-variance models can provide most optilam portfolio. In other hands, particle
swarm algorithm is best in client risk model. Most observations reflect the fact that in the problems which are with
complexity and size increases, the particle swarm algorithm perform better.