Foundations and Trends R in Optimization Vol. XX, No. XX (2017) 1–93 c 2017 DOI: 10.1561/XXXXXXXXXX The many faces of degeneracy in conic optimization last modified on May 9, 2017 Dmitriy Drusvyatskiy Henry Wolkowicz Department of Mathematics Faculty of Mathematics University of Washington University of Waterloo
[email protected] [email protected] Contents 1 What this paper is about 2 1.1 Related work . 3 1.2 Outline of the paper . 4 1.3 Reflections on Jonathan Borwein and FR . 4 I Theory 6 2 Convex geometry 7 2.1 Notation . 7 2.2 Facial geometry . 11 2.3 Conic optimization problems . 15 2.4 Commentary . 20 3 Virtues of strict feasibility 21 3.1 Theorem of the alternative . 21 3.2 Stability of the solution . 24 3.3 Distance to infeasibility . 27 3.4 Commentary . 28 4 Facial reduction 29 4.1 Preprocessing in linear programming . 29 ii iii 4.2 Facial reduction in conic optimization . 31 4.3 Facial reduction in semi-definite programming . 32 4.4 What facial reduction actually does . 34 4.5 Singularity degree and the Hölder error bound in SDP . 38 4.6 Towards computation . 39 4.7 Commentary . 40 II Applications and illustrations 42 5 Matrix completions 44 5.1 Positive semi-definite matrix completion . 44 5.2 Euclidean distance matrix completion, EDMC . 50 5.2.1 EDM and SNL with exact data . 54 5.2.2 Extensions to noisy EDM and SNL problems . 55 5.3 Low-rank matrix completions . 56 5.4 Commentary . 60 6 Hard combinatorial problems 61 6.1 Quadratic assignment problem, QAP .