(2000). A simple duality proof in convex quadratic programming with a quadratic con- straint, and some applications. European Journal of Operational Research 124 (1): 152-158. DOI: 10.1016/ S0377-2217(99)00173-3
其结果应用在凸二次规划(convex quadratic programming) 或 线性规划 (linear programming) 问题时是最理想化的。更进一步 … www.ntnu.edu.tw|基于3个网页 3. 凸二次规划问题 ... ) convex programming problem 凸规划问题 )Convex Quadratic Programming凸二次规划问题) nonsmooth problem 非光滑 … ...
Springer Series in Computational Mathematics Volume 22, 1994, pp 1-42 Convex and Quadratic Programming Boris N. Pshenichnyj $29.95 / €24.95 / £19.95 * Buy eBook Buy this eBook $69.99 / €67.82 / £56.99* * Final gross prices may vary according to local VAT. * Final gross...
We consider the optimization problem of scheduling a given set of jobs on unrelated parallel machines with total weighted completion time objective. This is a classical scheduling problem known to be NP-hard since the 1970s. We give a new and simplified version of the currently best-known ...
Each of these problems is a fractional programming problem involving the maximization of a ratio of a convex function to a convex function, where at least one of the convex functions is a quadratic form. First, the article presents and validates a number of theoretical properties of these ...
A dual active-set algorithm for convex quadratic programming Topics control optimization numerical-optimization quadratic-programming model-predictive-control active-set-method Resources Readme License MIT license Activity Stars 69 stars Watchers 6 watching Forks 13 forks Report repository Release...
Tsao, An unconstrained convex programming approach to solving convex quadratic programming problems. Optimization 27 (1993), 235-243.Fang, S. C. , and Tsao, H. S. J. , An Unconstrained Convex Programming Approach to Solving Convex Quadratic Programming Problems , Optimization, Vol. 27, pp. ...
QP is a self contained quadratic programming solver based upon the well known Goldfarb Idnani algorithm. Hessian factorization and orthogonal transformation are used every where (Householder and givens rotation) it is necessary. When equality constraints exist, only the reduced Hessian is required to ...
We cover the most important aspects for practically successful interior point methods for linear and convex quadratic programming in Chapter 3. Chapter 4 deals with ingredients for practically efficient feasible active set methods. Finally Chapter 5 provides a close description of our Lagrangian ...
Xiu, A convex quadratic semidefinite programming approach to the partial additive constant problem in multidimensional scaling, Journal of Statistical Com- putation and Simulation, 82 (2012), 1317-1336.H.-D. Qi,N. Xiu.A Convex Quadratic Semi-Definite Programming Approach to the Partial Additive ...