  This paper presents an implementation of the Imperialist Competitive
Algorithm (ICA) for solving the fuzzy random portfolio selection problem where
the asset returns are represented by fuzzy random variables. Portfolio
Optimization is an important research field in modern finance. By using the
necessity-based model, fuzzy random variables reformulate to the linear
programming and ICA will be designed to find the optimum solution. To show the
efficiency of the proposed method, a numerical example illustrates the whole
idea on implementation of ICA for fuzzy random portfolio selection problem.
