Approach for Solution of Nonlinear Optimization Problems with Blocks Structure and Coupling Constraint
DOI:
https://doi.org/10.20535/1810-0546.2015.5.65113Keywords:
Resource distribution problems, Optimization models, Non-linear programming methods, Decomposition algorithmsAbstract
Background. Non-linear optimization problems for the operation of large space or functionally distributed systems with independently functioning subsystems and restrictions on some of the common resources are considered.
Objective. The aim is to build an effective approach to solving nonlinear optimization problems of block structure with coupling constraints on the basis of the combination of approximating nonlinear optimization methods and decomposition techniques.
Methods. The three-step iterative scheme has been proposed. On the upper level the original problem is replaced by a sequence of approximating problems with additively-separable objective function and linear constraints. On the second level, coordinating problems, which are formed by the information received at the lowest level from local block problems, are solved.
Results. The algorithm, which is a combination of the linearization method of B.Pshenichniy and the dual decomposition, has been built. The structure of the dual coordination problem has been described. Estimation of the convergence rate has been carried out.
Сonclusions. The proposed approach and the algorithm constructed based on it can be applied to a wide range of problems associated with optimal allocation of limited resources in the large block-structured systems.References
L.S. Lasdon, Optimization Theory for Large Systems. Moscow, USSR: Nauka, 1975, 432 p. (in Russian).
V.I. Tsurkov, Decomposition in Problems of Large Dimension. Moscow, USSR: Nauka, 1981, 352 p. (in Russian).
P. Purkayastha and J. Baras, “An optimal distributed routing algorithm using dual decomposition techniques”, Commun. Inform. Systems, vol. 8, no. 3, pp. 277–302, 2008.
D. Goldfarb and S. Ma, “Fast multiple splitting algorithms for convex optimization”, SIAM J. Optimization, vol. 22, no. 2, pp. 533–556, 2012.
N. Komodakis et al., “MRF energy minimization & beyond via dual decomposition”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, is. 3, pp. 531–552, 2011.
B.N. Pshenichnyi and Y.M. Danilin, Numerical Methods in Extremal Problems. Moscow, USSR: Nauka, 1975, 319 p. (in Russian).
O.E. Kirik, “The linearization and the conjugate gradient algorithms for nonlinear network flow distribution problems”, Naukovi Visti NTUU “KPI”, no. 3, pp. 67–73, 2007 (in Ukrainian).
B.N. Pshenichnyi, Convex Analysis and Extremal Problems. Moscow, USSR: Nauka, 1980, 320 p. (in Russian).
O.E. Kirik and V.V. Ostapenko, “Optimal hydro resource distribution in the network structure irrigation systems”, Systemni Doslidzhennya ta Inform. Tekhnolohiyi, no. 4, pp. 79–90, 2010 (in Ukrainian).
V.M. Alexandrova and O.E. Kirik, “Optimization models and algorithms for network problems of resours’ distribution”, Naukovi Visti NTUU “KPI”, no. 5. pp. 39–45, 2014 (in Ukrainian).
Downloads
Published
Issue
Section
License
Copyright (c) 2017 NTUU KPI Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under CC BY 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
