https://pure.iiasa.ac.at/id/eprint/4577 2021-08-27T17:15:23Z info:eu-repo/semantics/descriptiveMetadata https://pure.iiasa.ac.at/id/eprint/4577/ Constraint Aggregation Principle in Convex Optimization Ermoliev, Y.M. Kryazhimskiy, A.V. Ruszczynski, A. A general constraint aggregation technique is proposed for convex optimization problems. At each iteration a set of convex inequalities and linear equations is replaced by a single inequality formed as a linear combination of the original constraints. After solving the simplified subproblem, new aggregation coefficients are calculated and the iteration continues. This general aggregation principle is incorporated into a number of specific algorithms. Convergence of the new methods is proved and speed of convergence analyzed. It is shown that in case of linear programming, the method with aggregation has a polynomial complexity. Finally, application to decomposable problems is discussed. WP-95-015 1995-02 Monograph NonPeerReviewed text en https://pure.iiasa.ac.at/id/eprint/4577/1/WP-95-015.pdf Ermoliev, Y.M. <https://pure.iiasa.ac.at/view/iiasa/338.html>, Kryazhimskiy, A.V. <https://pure.iiasa.ac.at/view/iiasa/1393.html>, & Ruszczynski, A. <https://pure.iiasa.ac.at/view/iiasa/1544.html> (1995). Constraint Aggregation Principle in Convex Optimization. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-95-015 info:eu-repo/semantics/objectFile info:eu-repo/semantics/humanStartPage