arXiv (Cornell University)
Sparse Convex Optimization Toolkit: A Mixed-Integer Framework
October 2022 • Alireza Olama, Eduardo Camponogara, Jan Kronqvist
This paper proposes an open-source distributed solver for solving Sparse Convex Optimization (SCO) problems over computational networks. Motivated by past algorithmic advances in mixed-integer optimization, the Sparse Convex Optimization Toolkit (SCOT) adopts a mixed-integer approach to find exact solutions to SCO problems. In particular, SCOT brings together various techniques to transform the original SCO problem into an equivalent convex Mixed-Integer Nonlinear Programming (MINLP) problem that can benefit from …