Genetic Algorithms for the Development of Queuing Networks

The article considers the problem of optimal scheduling of queueing networks based on the use of genetic algorithms. Offers a new special scheme of the chromosome encoding a functional crossover operators and mutations. The developed algorithms are generic for different types of queueing networks. Deterministic mutation is used to avoid premature convergence with a high accuracy. The use of genetic algorithms as applied to queueing implements the principle of hybrid systems and gives the possibility of future use of other mathematical devices in the development of the subject area. Proposed in the scheme, chromosome encoding significantly increase the accuracy and performance of the model. The results of computational experiments based on the developed algorithms with the distributed components are included for comparison of deterministic mutations with the classical probabilistic model.