Liu, Jiaqi2020-05-132020-05-1320202020-05-13http://hdl.handle.net/1828/11749In this project, we delve into an important class of constrained nonconvex problems known as mixed-integer quadratic programming (MIQP). The popularity of MIQP is primarily due to the fact that many real-world problems can be described via MIQP models. The development of efficient MIQP algorithms has been an active and rapidly evolving field of research. As a matter of fact, previously well-known techniques for MIQP problems are found unsuitable for large-scale or online MIQP problems where algorithm’s computational efficiency is a crucial factor. In this regard, the alternating direction method of multipliers (ADMM) as a heuristic has shown to offer satisfactory suboptimal solutions with much improved computational complexity relative to global solvers based on for example branch-and-bound. This project provides the necessary details required to understand the ADMM-based algorithms as applied to MIQP problems. Three illustrative examples are also included in this project to demonstrate the effectiveness of the ADMM algorithm through numerical simulations and performance comparisons.enAvailable to the World Wide Webproject