A Hybrid Approach to the Maximum Clique Problem in the Domain of Information Management

In this paper we observe the opportunity to offer new methods of solving NP-hard problems which frequently arise in the domain of information management, including design of database structures and big data processing. In our research we are focusing on the Maximum Clique Problem (MCP) and propose a new approach to solving that problem. The approach combines the artificial neuro-network paradigm and genetic programming. For boosting the convergence of the Hopfield Neural Network (HNN) we propose the genetic algorithm as the selection mechanism for terms of energy function. As a result, we demonstrate the proposed approach on experimental graphs and formulate two hypotheses for further research.