Constrained quadratic programming as a secondary m

yxfbbiedtj · Wysłany: Czw 15:05, 31 Mar 2011

Constrained quadratic programming as a method of secondary

By {. ) According to formula (4) computing (], etc. (5)) {by equation (6) assembly [surface and {q}) '{by Lemke algorithm for solving equation (7) may') 【)) ) and {。),{) and {x. ) Are sufficiently close to you?) ) A (),{。 )()'' ENDLOOP constrained quadratic programming first order approximation as the initial solution. 2 first-order approximation with constrained sequential quadratic programming (hereinafter referred to as c1 a SQP) comparison. Equation (3) can be rewritten as ix the first one ([] + class H ]) I (ix a}]) J-lJ-I - ((A3 +;[,(, tl (CH x +1) _-v J-ll {。}==( O, ..., O], the corresponding c1 a SQP method. (c (+ cm )_{)) 』-I array in real terms is revised goal target Hsian gradient (ie, the essence of Newton-Raphsoa method) and the constraints of first order approximation a linear combination of the gradient. For c1 A SQP method, constrained Hess; an array as the first order approximation only provides information. and this method in addition to the constraint Hessian matrix play a role in first-order Taylor approximation, also amended the goals and objectives of Hessian matrix gradient (This ensures that the target decreased more Taiwan Science),[link widoczny dla zalogowanych], amended the constraints of linear gradient group table (which is even more to ensure the feasibility of the design, which is a binding constraint region caused by a change order approximation of the compensation, because the constraints of the second order information through {.) for the right coefficient of the initiative to intervene in the direction). K-T conditions for the realization of optimal solutions to meet the necessary conditions; in the towel on its programming, it is necessary and sufficient conditions to ensure better convergence. The following numerical example shows that this law than the C1 - SQP method is more effective, Dian stability. AlgorithmforSolvingQuadraticProgrammingwithSecondOrder'ConstraintsSuiYunkang (ResearchInstituteofEngi ~ eerlngMe ~ Taa, aits.DUT) AbstractInordertosolvequadraticprogramming, withquadraticfunctionsofobecti4eandEonstraint ~. based0nKuhn-Tuckercoedition, akindofalgorithmofsequentialquadraticprogrammingwithsingleiteration, whichisinconsjderationoftheinf1aengeoftheconstraintSHessianmatrixupondirectionisadvancedinthispaper.AnumberofnumericalexperimentsshowthatthealgorithmhasmuchhigherSl ~ eedandmorestableCOOvergencythantheonethatisscquentia1quadraticprogrammingwithfirstorderapproximationoftheconstraints.KeyWords: quadraticprogrammingliterationmefhod / quadraticconstraintHeSSianmatrix Dalian University of Technology University ● pulp: _ the state seal state cancer plan horseleech Gu Xin Lin Rights stubble file Alice Lam laugh toad frog sounds of earthworms.. ∞ -'---- mad blood r × 1,4 Lei shoes summer summer clamor can offer banner Lu beast Chang Shu suddenly lack the amount of control the amount of mushroom Gu Zeng g sugar dish pan f beast = Lu Yu} din dragonfly photo miscellaneous plan -. I. - twenty-two .- familiar words of the!! Fortunately, I Gu State: 1,4: Fortunately, the main arms - I left foot in Gui Lu Qian 1,4 1,4 + left foot ten! -0 with l wang: 1,4:1,4 + + + suppressive debate Ji Zhi # ∞ I despair. 忸 turn pan Mount Cameroon v seven vertical stack plot