BIOINSPIRED SEARCH IN THE COMPLETE GRAPH OF A PERFECT MATCH OF MAXIMUM POWER
Б.К. Лебедев, Oleg Borisovich Lebedev, Marina Ganzhur, Maxim I. Beskhmelnov · Известия Южного федерального университета. Технические науки · 2025
A reconfigurable architecture of a hybrid multi-agent decision-making system based on swarm algorithmparadigms has been developed. The reconfigurable architecture allows implementing the followinghybridization methods by tuning: high-level and low-level hybridization by nesting, preprocessor/postprocessor type, co-algorithmic based on one or several types of algorithms. A methodology forsynthesizing a perfect matching of minimum weight in a complete graph based on the basic principles ofhybridization of search. evolutionary procedures has been proposed. In this paper, the swarm agents aretransforming chromosomes, which are the genotypes of the solution. An ordered list of the set of graphvertices is used as the solution code. A structure of an ordered matching code has been developed, themain advantage of which is that one solution (matching) corresponds to one code and vice versa. Theproperties of the ordered code have been determined and encoding and decoding algorithms have beendeveloped. The hybrid system operation starts with the random generation by a swarm of bees of an arbitraryset of solutions differing from each other in the form of an initial set of chromosomes. The key operationof the bee algorithm is the study of promising solutions and their neighborhoods in the search space.A method for forming neighborhoods of solutions with an adjustable degree of similarity and closenessbetween them has been developed. At subsequent stages of the multi-agent system operation, solutions aresearched for by procedures built on the basis of hybridization of the swarm and ant algorithms. A distinctivefeature of hybridization is the preservation of the autonomy of the hybridized algorithms. Note that asingle data structure is used to represent solutions in the algorithms, which simplifies the docking of thedeveloped procedures. An approach to constructing a modified paradigm of a swarm of transformingchromosomes is proposed. The search for solutions is performed in an affine space. In the process ofsearching, permanent transformations (transitions) of chromosomes into states with the best value of theobjective function of the solution (gradient strategy) are carried out. The process of finding solutions isiterative. At each iteration, the chromosomes are transformed (transitioned) into states with better valuesof the objective function of the solution. The purpose of transforming a chromosome that tends to be thebest chromosome into a new state is to minimize the degree of difference by changing the mutual arrangementof elements in an ordered list, which corresponds to an increase in the weight of the affineconnection. The chromosomes updated after the transformation are, in turn, the base points in subsequenttransformations. As a result of the experiments, it was found that the quality indicators of the developedalgorithms have higher values than in the works presented in the literature.