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An Algorithm for Strictly Convex Quadratic Programming with Box Constraints
作者姓名:XIAOJUN LIU  YONG-CHANG JIAO  SATORU FUJISHIGE
摘    要:1IntroductionWeconsiderastrictlyconvex(i.e.,positivedefinite)quadraticprogrammingproblemsubjecttoboxconstraints:t-iereA=aij]isannxnsymmetricpositivedefinitematrix,andb,canddaren-vectors.Letg(x)bethegradient,Ax b,off(x)atx.Withoutlossofgeneralityweassumebothcianddiarefinitenumbers,ci

An Algorithm for Strictly Convex Quadratic Programming with Box Constraints
XIAOJUN LIU, YONG-CHANG JIAO, SATORU FUJISHIGE.An Algorithm for Strictly Convex Quadratic Programming with Box Constraints[J].OR Transactions,1998(1).
Authors:XIAOJUN LIU  YONG-CHANG JIAO  SATORU FUJISHIGE
Institution:XIAOJUN LIU; YONG-CHANG JIAO; SATORU FUJISHIGE
Abstract:We propose an efficient algorithm for solving strictly convex quadratic programs with box constraints (i.e., lower and upper bounds on each variable). our algorithm is based on the active set and the Newton method. We repeatedly compute relevant inverse matrices efficiently and, starting from an initial feasible poillt, we find an optimal solution of the problem in finitely many steps. Our experimental results show that the new algorithm is practically efficient.
Keywords:Quadratic programming  algorithm  active set method  Newton method  box constraints
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