Аннотация:
The object of the study is decision support systems. The subject of
the study is the decision-making process in management problems using
a combined bio-inspired algorithm,
consisting of:
– the improved wolf optimization
algorithm and the improved sparrow
search algorithm – for solving optimization problems regarding the object
state;
– an advanced genetic algorithm –
for selecting the best agents in flocks;
– an advanced training method –
for deep training of agents to improve the optimization characteristics
of agents.
A solution search method using
an improved bio-inspired algorithm is
proposed. The method has the following sequence of actions:
– input of initial data;
– initialization of the search for a
flock of sparrows and its parameters;
– ranking and selection of sparrow agents using an advanced genetic
algorithm;
– updating the sparrow location
for the discoverer;
– checking the conditions for updating the position of sparrows;
– initialization of additional search
parameters;
– running the gray wolf optimization algorithm;
– training agents’ knowledge bases;
– determining the amount of necessary computing resources of the
intelligent decision support system.
The originality of the proposed method lies in the combined use of bio-inspired algorithms, setting agents taking into account the uncertainty of
the initial data, advanced global and
local search procedures. The method
makes it possible to increase the efficiency of data processing at the level of
19 % using additional improved procedures. The proposed method should be
used to solve the problems of evaluating complex and dynamic processes in
the interest of solving national security problems
