The Application of Imperialist Competitive Algorithm for Fuzzy Random Portfolio Selection Problem

نویسندگان

  • Mir Ehsan Hesam Sadati
  • Jamshid Bagherzadeh Mohasefi
چکیده

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.

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عنوان ژورنال:
  • CoRR

دوره abs/1402.4834  شماره 

صفحات  -

تاریخ انتشار 2013