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Optimal Algorithm for Optimization Problems with Special Restriction

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dc.contributor.author GĂRLĂ, Eugeniu
dc.date.accessioned 2020-11-03T16:41:48Z
dc.date.available 2020-11-03T16:41:48Z
dc.date.issued 2018
dc.identifier.citation GĂRLĂ, Eugeniu. Optimal Algorithm for Optimization Problems with Special Restriction. In: CAIM 2018: The 26th Conference on Applied and Industrial Mathematics: Book of Abstracts, Technical University of Moldova, September 20-23, 2018. Chişinău: Bons Offices, 2018, p. 59. en_US
dc.identifier.uri http://repository.utm.md/handle/5014/11077
dc.description Only Abstract en_US
dc.description.abstract The present paper analyses a class of nonlinear optimization problems with special restrictions, we propose a direct method for solving the auxiliary problem, for which we calculate complexity, we also assesses the maximum number of elementary operations and describe the optimal algorithm for performing numerical calculations. The study builds an optimal algorithm for solving the auxiliary problem of PG model; the complexity of this algorithm is O(nm2, N), the number of elementary operations is minimal. Matrix inversion does not depend on the size of problem n and always has constant size - m × m and the operation complexity is O(m3). In practical situations, if m << n, then the value of m2 is much smaller than the value of n, thus can be considered as a constant, resulting the complexity is O(n2), in other words it’s almost the same as for the approximation methods. Thus, the model PG is fully functional and practically ”immune” to the size of the optimization problem. en_US
dc.language.iso en en_US
dc.publisher Bons Offices en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject algorithm complexity en_US
dc.subject optimization methods en_US
dc.title Optimal Algorithm for Optimization Problems with Special Restriction en_US
dc.type Article en_US


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