GENETIC ALGORITHMS AS A TOOL FOR SOLVING OPTIMIZATION PROBLEMS

Abstract

Genetic algorithms as a heuristic method, based on the principles of natural selection, can successfully be applied in the modeling of nonlinear optimization problems with nonlinear objective functions, including cases where these functions do not satisfy the conditions for continuity, and what is more the arguments can be both discrete and continuous variables.

Constructing a portfolio is a major task in making financial investment decisions. In this task, the an objective function is been optimized to obtain shares of the portfolio assets which maximize return and minimize risk of the investment. This article is a brief overview of genetic algorithms and a concept for their application for constructing optimal portfolio is proposed.