Comparison of Simulated Annealing and Electromagnetic Algorithms for Solution of Extended Portfolio Model

This paper presents two meta-heuristic algorithms to solve an extended portfolio selection model. The extended model is based on the Markowitzʹs Model, aiming to minimize investment risk in a specified level of return. In order to get the Markowitz model close to the real conditions, different constraints were embedded on the model which resulted in a discrete and non-convex solution space. However, due to the NP-hard nature of the problem; two meta-heuristic algorithms were used, namely the simulated annealing and electromagnetic algorithms. Comparative result indicated high efficiency of the extended model and the solution presented by the electromagnetic algorithm.