In the science of operation research and decision theory, selection is the most important process.Selection is a process that studies multiple qualitative and quantitative criteria, related to the science of management, which are mostly incompatible with each other. The multi criteria selection of a renewable energy portfolio is one of the main issues considered in multi criteria literature. In the present study to form a portfolio of renewable energy, first, the KOHONEN neural network algorithm was used, and then each portfolio was evaluated using multi criteria decision-making methods.Further, through meta heuristic multi objective algorithms Pareto rank analysis was conducted and social acceptance of renewable energy production methods was assessed. Finally, the portfolio for studied energies was composed. The results indicated that Cuckoo Search Algorithm and Grey Relational Analysis are effective and efficient for the selection of optimal Pareto portfolio of renewable energy.