Problem-oriented knowledge processing on the basis of hybrid approach

The paper discusses a hybridization of adaptation mechanisms with self-organization in order to process problem-oriented knowledge. The core of the proposed method consists in sequential execution of bionic and genetic algorithms. To demonstrate the hybrid algorithm we gave an example of a solution search. In the paper it is presented a formulation of the problem-oriented knowledge processing task during the optimal solution search. To solve this problem we developed a modified architecture of the hybrid search. The suggested architecture involves principal components of a bioinspired search. To improve the algorithm performance we provide an opportunity to add new algorithms with an evolutionary adaptation module and environment module.. Conducted experiments confirmed that time complexity of the developed approach is polynomial.