Abstract
New technologies, principles and mechanisms of solving the cover problem are proposed. Based on simulating evolution processes, they are developed using the general approach that combines the principles of adaptation by self-learning, self-organization, and genetic search. The cover problem is analyzed and the compact representation of the solution in the form of the matrix of boundary requirements is constructed. This allowed forming the space of solutions with the adaptive search process organized within it. Experimental tests were conducted on an IBM PC. When compared to known algorithms, the solutions obtained by the adaptive search algorithm proved to have better (smaller) values of the objective function by 6–9% on average.
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