Presents 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
In article the problem of development of algorithm of bionic search for tasks about an extreme way on the column is considered. Now development of effective methods and algorithms for problems of this type is carried out many years, being on - former an actual problem. Development of bionic algorithms on the basis of evolutionary strategy is perspective, especially at the solution of labor-consuming problems of optimization. It is possible to carry to advantages: possibility of performance of evolutionary and genetic search, and also that OH consists in parallel generation of sets of quasioptimum alternative decisions with possible "migration" of decisions between these sets. Realization of the general strategy of adaptation of the size of population by use of sequence of a sieve of Eratosfen, allowing to adapt for characteristics of bionic search is offered.
Keywords: evolution, bionic algorithm, task about an extreme way, adaptation