Solution of task on the minimum cost data flow based on bionic algorithm

Abstract

Abstract The paper presents the solution of task on the minimum cost data flow in static and dynamic setting based on evolutionary algorithms. The distinctive feature of the algorithm is the use of joint evolution, choice of evolution models (use of micro-, macro- and metaevolutions), adjustment to external environment, hierarchical management of genetic and evolutionary search, local search of solutions and application of all modified genetic operators based on evolutionary strategy and search methods. The paper illustrates the example of task on the recommended data flow and a method of adjusting the data transfer process to recommended parameters.