It is shown that the problem of simultaneous processing of dynamic information arrays of different degrees of structure and fuzziness is currently relevant. One of the prototypes of mathematical models containing such information structures is the problem of practical distribution of resources in the conditions of possible, difficult to formalize effects. In this problem there are two factor for the rational allocation of resources: network bandwidth to operating conditions and the preference of the routes of transmission resources on the network in terms of the alleged destructive effects. The high degree of uncertainty inherent in the process reduces the feasibility of resource-intensive distribution algorithms. At the same time, it is necessary to obtain a variety of alternative solutions with diversity in terms of resistance to possible impacts. Since, if all routes pass through one transit node, all of them will be equally exposed to the threats of impact inherent in this node, and when it fails, there will be no alternative routes, which will require re-search of routes for the transfer of resources. Fast heuristics, based, for example, on greedy approaches, can not provide the proper diversity, therefore, even with clear formulations of optimization problems, fall into local Optima. For this reason, it is advisable to Supplement the initial solution formation procedure with borrowed solutions from the previously considered problems. In order to improve the solutions obtained at the stage of formation of the starting population, and to ensure the diversity of the descendants of these solutions, describing the routes of resource transfer, an evolutionary algorithm for finding the set of the shortest time routes of resource transfer. The peculiarity of the process of solving the problem proposed algorithm is to maintain the diversity of the population of solutions to possible threats.
Keywords: intelligent algorithm, distribution, fuzzy space, adaptation, transport networks
The cryptanalysis task with use of new model of optimizing strategy – the combined bioinspired algorithm is considered. Application of the combined bioinspired algorithm (a genetic algorithm and an algorithm of ant colonies) for realization the cryptanalysis of shifts codes is described. The description of the combined algorithm is provided, his distinctive features are noted, the demonstration example of realization the cryptanalysis the ciphered text line is described by this algorithm. In relation to this algorithm it is shown that the probability of receiving an optimal variant of the decision at realization of combined cryptanalysis algorithms can't be less probability of obtaining the optimal solution when using of the classical bioinspired algorithms.
Keywords: Cryptanalysis, the bioinspired algorithms, genetic algorithm, algorithm of bee colonies, a crossingover, a mutation, the code of shifts
The aim of this work is to develop a model of the agent changing its own structure, and movable in the fuzzy heterogeneous search space. The need of creating these search tools solutions is caused not only by lack of data on the solved optimization tasks, but also complex computational structures used in modern information systems. The agent is represented as a point in a fuzzy heterogeneous search space, the scale of each axis of the space built on the basis of the corresponding fuzzy sets. The movement of the agent along each axis is based on the permissible operations on the elements of the corresponding fuzzy sets. An example of agent movement along the axis specified on the basis of S-fuzzy sets. To determine the stopping agent developed automatic adaptation. It is shown that changing the position of the agent in the search space not always leads to the change of uncertainty inherent in the decision, described by the agent. The novelty of the approach is to develop adaptive algorithms move the agent in a heterogeneous search space. On the basis of machine adaptation is shown the scheme of movement of the agent in fuzzy search space along the axis specified with S - fuzzy sets.
Keywords: intelligent agent, heterogeneous structures, fuzzy space, adaptation, S-fuzzy set, automatic adaptation
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
One of the components of the optimization problem is a set of constraints describing the basic requirements for solutions. So as to find a solution that fully satisfies all the wishes of the experts, it is not always possible, the search area extends through analysis of semi-feasible solutions. The adjustment of the system constraints may contribute to changes in the structure and appropriateness of the decisions. The paper shows the ways to form a generalized membership functions of vague constraints of optimization problems based on the logics of Reichenbach and Lukasiewicz. It is known that for the same design procedures in some cases it is necessary to obtain accurate solutions, while others just get approximate solutions. Therefore, we analyzed the features of membership functions obtained using these logics. It is shown that by implication deny rules to allow logic-based Reichenbach membership function takes values equal to one if the value of the function allow rule is one, or if the value of the function deny rule is zero. By implication deny rules in allowing based on Lukasiewicz logic membership function takes values equal to one if the value of the function allow rule is greater than the value of the function deny rules. Therefore, it can be argued that when designing systems with increased reliability (precision) is more expedient to use the function implications for Reichenbach deny rules in a permissive compared with the same implication by Lukasiewicz. The implication deny rules to allow for the Lukasiewicz appropriate to use when designing subsystems that perform secondary functions that are not systemically forming, etc.
Keywords: adaptation, fuzzy system, the implication, intellectual method, membership function, optimization, logic, Reichenbach, Lukasiewicz logic