Journal
MATHEMATICAL PROGRAMMING
Volume 164, Issue 1-2, Pages 55-90Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s10107-016-1072-9
Keywords
Feasible method; Nonconvex problem; Nonsmooth optimization; Parallel and distributed implementation; Green communications
Categories
Funding
- USA National Science Foundation (NSF) [CIF 1564044, CCF 1632599]
- CAREER [1555850]
- Office of Naval Research (ONR) [N00014-16-1-2244]
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [1632599, 1564044] Funding Source: National Science Foundation
- Div Of Electrical, Commun & Cyber Sys
- Directorate For Engineering [1555850] Funding Source: National Science Foundation
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We propose a general feasible method for nonsmooth, nonconvex constrained optimization problems. The algorithm is based on the (inexact) solution of a sequence of strongly convex optimization subproblems, followed by a step-size procedure. Key features of the scheme are: (i) it preserves feasibility of the iterates for nonconvex problems with nonconvex constraints, (ii) it can handle nonsmooth problems, and (iii) it naturally leads to parallel/distributed implementations. We illustrate the application of the method to an open problem in green communications whereby the energy consumption in MIMO multiuser interference networks is minimized, subject to nonconvex Quality-of-Service constraints.
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