Adaptive bionic algorithm for solving the problem of data flow minimum cost
Abstract
Adaptive bionic algorithm for solving the problem of data flow minimum cost
Incoming article date: 04.04.2016Presents an adaptive algorithm for solving the data flow of minimum cost in a static and a dynamic formulation. In the dynamic formulation of the problem change the matrix describing the network. An important component of the algorithm is to use the ideas of co-evolution, the choice of models of evolution (micro-, macro-, meta-evolution), adaptation to the external environment, hierarchical management of genetic and evolutionary search, local search solutions and the use of all modified by genetic operators based on greedy strategies and search methods. Given the example of the recommended data flow based on a known formula the definition of fuzzy proximity µx(b) variable b to the specified value. The adjustment of the process data under the recommended settings implemented with the help of machines adaptation. A distinctive feature of the algorithm is the use of machines adapted for determining the need for and the method of modifying intermediate solutions, as well as for a decision about modifying the previously obtained solutions.
Keywords: data flow, adaptation, evolution, optimization, evolutionary search