Genetic algorithms and methods of optimal enterprise management
DOI:
https://doi.org/10.34185/1562-9945-5-166-2026-15Keywords:
genetic algorithm, CAPEX, NPV, optimization, systems analysis, Cobb-Douglas production function, investment strategy, project analysis, evolutionary computingAbstract
The article presents the results of a study aimed at optimizing the distribution of capital investments of an industrial enterprise using a genetic algorithm. A mathematical model has been developed in which the shares of investments are distributed among five subsystems – resources, equipment, technology, economy and organization, which are determined by evolutionary search for the optimal financing vector. The fitness function is given in the form of net present value (NPV), which allows directly taking into account the value of money.
The purpose of the work is to develop, implement and analytically evaluate a model for optimizing the distribution of capital investments of an industrial enterprise based on a genetic algorithm, which allows maximizing the net present value (NPV) under conditions of limited resources and nonlinear interaction between production subsystems.
The methodology. The methodological basis of the study is a combination of systems analysis, evolutionary calculations and economic and mathematical modeling, which provides a comprehensive study of the processes of capital investment distribution in multifactor production systems. The methodology involves multilevel verification of the stability of the model through repeated experiments, comparison with basic linear models and statistical analysis of variations of the results.
The scientific novelty. The scientific novelty of the obtained results lies in the formation of a new evolutionary-optimization paradigm for managing the investment activities of industrial enterprises, which combines genetic algorithms, economic dynamics, and systems analysis.
Conclusions. A model for optimizing the allocation of capital investments based on a genetic algorithm has been developed and tested, which ensures the maximization of net present value (NPV) in a multi-parameter system.
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