HOPDM is a package for solving large scale linear, convex quadratic and convex nonlinear programming problems. The code is an implementation of the infeasible primal-dual interior point method. It uses multiple centrality correctors; their number is chosen appropriately for a given problem in order to reduce the overall solution time. HOPDM automatically chooses the most efficient factorization method for a given problem (either normal equations or augmented system). The code compares favourably with commercial LP, QP and NLP packages.
HOPDM has been written by Jacek Gondzio. An extension for convex QP has been developed together with Anna Altman. An extension for convex NLP has been developed together with Olivier Epelly (see NLPHOPDM). A decomposition environment based on HOPDM has been developed together with Robert Sarkissian. It is called PDCGM which stands for Primal-Dual Column Generation Method. Special thanks go to Marek Makowski for help in a development of the C version of the code.