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MODELS, METHODS, SOFTWARE AND PRACTICAL APPLICATIONS FOR COMPLEX PROBLEMS OF CHOOSING OPTIMUM DECISIONS:
- Development of effective models and methods for the analysis of multiextremal problems of decision-making, including parallel methods for high-performance cluster systems;
- Development of parallel program systems of global optimization;
- Solution of important applied problems of global search.
Main results:
Leading experts:
Main technological and research equipment:
Main partners and customers:
Key projects (sources of financing):
Main publications:
Main results (comparable with the best world analogues):
- Effective algorithms for solving unconditional problems of global optimization have been developed;
- A scheme has been developed for separate account of restrictions (without using the ideas of the method of penal functions) that reduces computing load and permits partial definiteness and computability of the functionals characteristic for applications;
- Algorithms have been developed for reducing the dimension of problems by means of a set of Peano curves (multiple manifolds) that convey the property of affinity in a multidimensional space to one-dimensional scales. The algorithms have found application in optimization and pattern recognition;
- Methods of uniform approximation of weakly effective sets of multicriterial problems have been developed (where the set of weakly effective solutions is the object of uniform convergence of the procedures);
- Ways have been developed for accelerating the convergence of global optimization methods by taking into account the degree of the problem regularity determined on the basis of the introduced concept of e- reserved solutions, and also by using the adaptively variable procedure for testing the restrictions;
- Methods for effective parallelization of the process of choice in multiprocessing environments (non-redundant parallel optimization) have been developed. The methods have been realized in the program system of multiextremal optimization GlobalExpert;
- Many practical problems have been solved in which the choice of decisions is described by the statement of multiextremal optimization problems.
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Leading experts:
- Roman Grigorievich Strongin, D.Sc. (Physics and Mathematics), Professor;
- Victor Pavlovich Gergel, D.Sc. (Engineering)., Professor;
- Yaroslav Dmitrievich Sergeev, D.Sc. (Physics and Mathematics), Professor;
- Vladimir Aleksandrovich Grishagin, Cand.Sc. (Physics and Mathematics), Assoc. Professor.
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Main technological and research equipment:
- High-performance computing cluster installed at the University of Nizhni Novgorod in the framework of the priority national project "Education" comprising 64 dual-processor servers, (128 dual-core processors), Intel Xeon 5150 2,66 GHz, 4GB DDR2-667 FB-DIMM RAM, 80 GB HDD, 2 õ Gigabit Ethernet; total number of processors - 128, kernels - 256, peak performance – 2700 Gflops.
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Main partners:
- Computer center of the Russian Academy of Sciences;
- Delft Technical University ( Netherlands );
- University of Calabria (Italy).
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Key projects (sources of financing):
- Project Ê 0392 of the Federal target program "Integration" 1998-2000.
- Project 0201.03.287 under the State Contract 0201.03.287 within the framework of the Federal Target Scientific and Technical program «Research and development in priority directions of development of science and engineering for civil purposes» (Subprogram «Promising information technologies»).
- Projects of the Russian Foundation for Basic Research Nos. 95-01-01073, 01-01-00587, 07-01-00467.
- Grant No. NSh.-4694.2008.9 of the Council for Grants of the President of the Russian Federation for the State support of leading scientific schools of the Russian Federation.
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Main publications:
- Strongin R.G., Sergeev Ya. D. (2000). Global optimization with non-convex constraints: Sequential and parallel algorithms. Kluwer Academic Publishers, Dordrecht.
- Gorodetsky S.Yu., Grishagin V.A. Nonlinear programming and multiextremal optimization. N.Novgorod: Publishing house of the Nizhni Novgorod State University , 2007. – 489 Pp.
- Sergeev Ya.D., Kvasov D.E. Diagonal methods of global optimization. – Ì.: Fizmatlit, 2008. – 352 Pp.
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