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Simplex embedding method in decomposition of large sparse convex nondifferentiable optimization problems

Kolosnitsyn A. Simplex embedding method in decomposition of large sparse convex nondifferentiable optimization problems // CEUR Workshop Proceedings. Vol.2098. 2018. P.189-199. We consider an adaptation of the simplex embedding method to the decomposition of large-scale convex problem with sparse block-wise constraint matrix. According to the Lagrangean relaxation technique such problem is reduced to the maximization of nondifferentiable concave function with subgradient that can be easily calculated...

Теги: decomposition , lagrangean relaxation , nondifferentiable optimization , simplex embedding method , optimization , concave function , convex problems , embedding method , non-differentiable , non-differentiable functions , non-differentiable optimization , numerical
Раздел: ИСЭМ СО РАН
Modified simplex imbeddings method in convex non-differentiable optimization

Kolosnitcyn A. Modified simplex imbeddings method in convex non-differentiable optimization // CEUR Workshop Proceedings. Vol.1623. 2016. P.226-233. We consider a new interpretation of the modified simplex imbeddings method. The main construction of this method is a simplex which contains a solution of convex ...

Теги: modified simplex imbeddings method , self-concordant barrier , structural optimization , geometry , operations research , optimization , cutting planes , non-differentiable , non-differentiable optimization , numerical experiments , optimal solutions , self-con
Раздел: ИСЭМ СО РАН


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