An Interior-Point Algorithm for Nonconvex Nonlinear Programming Export

@article{vanderbei:99a, abstract = {The paper describes an interior-point algorithm for nonconvex nonlinear programming which is a direct extension of interior-point methods for linear and quadratic programming. Major modifications include a merit function and an altered search direction to ensure that a descent direction for the merit function is obtained. Preliminary numerical testing indicates that the method is robust. Further, numerical comparisons with MINOS and LANCELOT show that the method is efficient, and has the promise of greatly reducing solution times on at least some classes of models.}, author = {Vanderbei, Robert J. and Shanno, David F.}, citeulike-article-id = {3865880}, citeulike-linkout-0 = {http://dx.doi.org/10.1023/A:1008677427361}, citeulike-linkout-1 = {http://www.springerlink.com/content/m2841224u2141726}, day = {21}, doi = {10.1023/A:1008677427361}, journal = {Computational Optimization and Applications}, keywords = {linear-programming, optimization, quadratic-programming}, month = {April}, number = {1}, pages = {231--252}, posted-at = {2009-01-08 23:20:27}, priority = {0}, title = {An Interior-Point Algorithm for Nonconvex Nonlinear Programming}, url = {http://dx.doi.org/10.1023/A:1008677427361}, volume = {13}, year = {1999} }

TY - JOUR ID - vanderbei:99a L3 - citeulike-article-id:3865880 N2 - The paper describes an interior-point algorithm for nonconvex nonlinear programming which is a direct extension of interior-point methods for linear and quadratic programming. Major modifications include a merit function and an altered search direction to ensure that a descent direction for the merit function is obtained. Preliminary numerical testing indicates that the method is robust. Further, numerical comparisons with MINOS and LANCELOT show that the method is efficient, and has the promise of greatly reducing solution times on at least some classes of models. IS - 1 JF - Computational Optimization and Applications EP - 252 TI - An Interior-Point Algorithm for Nonconvex Nonlinear Programming VL - 13 SP - 231 KW - linear-programming KW - optimization KW - quadratic-programming AU - Vanderbei, Robert AU - Shanno, David PY - 1999/04/21/ UR - http://dx.doi.org/10.1023/A:1008677427361 ER -