Twitter Google Share on Facebook CQP (redirected fromConvex Quadratic Programming) Category filter: AcronymDefinition CQPCertificat de Qualification Professionnelle(French: Certificate of Professional Qualification) CQPConvex Quadratic Programming CQPCalifornia QSO Party ...
We propose a branch-and-bound algorithm for minimizing a not necessarily convex quadratic function over integer variables. The algorithm is based on lower bounds computed as continuous minima of the objective function over appropriate ellipsoids. In the nonconvex case, we use ellipsoids enclosing the...
linearorotherconvexobjectivefunctions.However,thenonconvexcasesarethemorefrequentlyoccurringinpractice,whicharemoredifficulttohandlethantheconvexone.Inthispaper,aclassofinventorycontrolwithnonconvexquadraticobjectiveisconsidered.TheLagrangedecompositionmethodisusedforgeneratingconvexrelax-ationsforthenonconvexquadratic...
The problem of minimizing a quadratic objective function subject to one or two quadratic constraints is known to have a hidden convexity property, even when the quadratic forms are indefinite. The equivalent convex problem is a semidefinite one, and the equivalence is based on the celebrated S-...
Convex reformulation for binary quadratic programming problems via average objective value maximization 来自 Semantic Scholar 喜欢 0 阅读量: 59 作者:C Lu,X Guo 摘要: Quadratic convex reformulation is an important method for improving the performance of a branch-and-bound based binary quadratic ...
A randomized primal distributed algorithm for partitioned and big-data non-convex optimization In this paper we consider a distributed optimization scenario in which the aggregate objective function to minimize is partitioned, big-data and possibly n... I Notarnicola,G Notarstefano,I Notarnicola,...
Our resulting relaxation does not use significantly more variables than the original problem, in contrast to many other relaxations based on lifting. The corresponding separation problem is a highly structured semidefinite program (SDP) with convex but non-smooth objective. We propose to solve this ...
‘tr_VV_sum’ is the objective function and is calculated by the following code %% 目标函数 tr_VV_sum = 0 ; for i = 1:(K+J) tr_VV{i} = square_pos(norm(V_i{i,:},‘fro’)) ; tr_VV_sum = tr_VV_sum + square_pos(norm(V_i{i,:},‘fro’)) ; ...
aClassofnonconvexquadraticallyconstrainedquadraticprogram- mingproblemsgeneralizedfromrelaxationsofquadraticassignmentproblems.Weshowthateach problemispolynomiallysolved.Strongdualityholdsifaredundantconstraintisintroduced.Asan application,anewlowerboundisproposedforthequadraticassignmentproblem. Keywords Nonconvexprogramming,...
On the convergence properties of a majorized ADMM for linearly constrained convex optimization problems with coupled objective functions In this paper, we establish the convergence properties for a majorized alternating direction method of multipliers (ADMM) for linearly constrained convex o... C Ying,X...