This paper presents a new method for selection of optimal options portfolios. The problem of defining optimal portfolios of real options is formulated as integer programming. The algorithm of generating an optimal portfolio of real options is also presented. The incremental benefit of portfolio of real options is valued using Monte Carlo simulation and modeling the prices and demand as Geometric Brownian Motion. The presented method allows to select optimal portfolios of real options with consideration of statistical and qualitative dependences of options. The results show that real options can generate a significant increase in the net present value (NPV).

In the context of globalization and fierce competition in world markets, the high level of investment activity in the country is a key to economic and innovative development. The high level of wear and tear of fixed assets in developing countries gives special relevance to solving the problem of attracting investments for production development. Hence, for the investment management system choosing an optimal variant among several available investment projects is one of the most responsible stages of ensuring the stable operation and sustainable development of an enterprise. In this regard, the aim of the article is to develop a comprehensive multi-criteria approach to choose the best investment option. The article analyzes the existing methodological approaches to assess the economic efficiency of the investment projects, identifies their advantages and disadvantages. A multi-criteria method of investment project evaluation is proposed, which is characterized by the absence of restrictions on the number of individual evaluation indicators and the possibility for the investor to determine the significance of every indicator using weights independently. The use of the proposed methodology by enterprises will improve the quality of management decisions at the stage of choosing the optimal investment option.

This paper was retracted based on the authors' request due to errors in the computations.