Izvestiya of Saratov University.
ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)

multiextreme criterion function

The Effectiveness Analysis of Several Parallel Algorithms Based on Simulated Annealing Method of Global Optimization Problem Solving

This article presents the results of the development of a parallel computing system and testing its capabilities applied to solving scientific and educational problems. Three parallel variants of the simulated annealing algorithm are proposed and implemented for multiextreme criterion function of two variables with explicit constraints. The reliability and performance of parallel versions of the algorithm, depending on their parameters and the number of working nodes in parallel computing system, is investigated.

The application of optimization algorithm using simulated annealing method for parallel computing systems

This article presents the results of the adaptation algorithm for searching the global minimum of multiextreme criterion function of great count of variables with constraints based on the method of simulated annealing algorithm for systems of parallel and distributed computing. The reliability of the searching global minimum, depending on the number of nodes of parallel computer system is investigated.

The parallel variant of conditional optimization algorithm with Box complex method

This article presents the results of the adaptation algorithm for global extremum searching with presence explicit and implicit constraints complex method created by Box for systems of the distributed and parallel computing. The optimal count of nodes of computing system from the point of view of reliability a global extremum finding and time of its search is defined.

The Application of a Genetic Algorithm to Global Optimization Problem Solving on Parallel and Distributed Computing Systems

This article presents the results of the adaptation of method of searching the global minimum of multiextremal criterion function of multiple variables with constraints based on genetic algorithm for parallel and distributed computing systems. Two variants of genetic algorithm parallelization are proposed. The reliability and performance of parallel versions of an algorithm, depending on its parameters and the number of nodes in parallel computer system is investigated.