Conic Linear Programming Yinyu Ye December 2004, revised January 2015 i ii Preface This monograph is developed for MS&E 314, \Conic Linear Programming", which I am teaching at Stanford. Information, lecture slides, supporting mate- rials, and computer programs related to this book may be found at the following address on the World-Wide Web: http://www.stanford.edu/class/msande314 Please report any question, comment and error to the address:
[email protected] A little story in the development of semidefinite programming (SDP), a major subclass of conic linear programming. One day in 1990, I visited the Computer Science Department of the University of Minnesota and met a young graduate student, Farid Alizadeh. He, working then on combinatorial optimiza- tion, introduced me “semidefinite optimization" or linear programming over the positive definite matrix cone. We had a very extensive discussion that afternoon and concluded that interior-point linear programming algorithms could be ap- plicable to solving SDPs. I suggested Farid to look at the linear programming (LP) interior-point algorithms and to develop an SDP (primal) potential reduc- tion algorithm. He worked hard for several months, and one afternoon showed up in my office in Iowa City, about 300 miles from Minneapolis. He had every- thing worked out, including potential function, algorithm, complexity bound, and even a \dictionary" list between LP and SDP. But he was stuck on one problem that was on how to keep the symmetry of the scaled directional ma- trix. We went to a bar nearby on Clinton Street in Iowa City (I paid for him since I was a third-year professor then and eager to demonstrate that I could take care of my students).