Mixed-integer Convex Optimization
Mixed-Integer Convex Optimization is a mathematical optimization framework that belongs to the class of integer programming problems, distinguished by the requirement that discrete variables may appear alongside continuous variables in a convex optimization problem, where the objective function and constraint set are convex when integer variables are fixed.
196
Publications
13.4K
Citations
580
Authors
281
Institutions
Publications per year
2017–2026
134
Variants
MicpMixed-integer Convex Programming
Parents
196
An algorithmic framework for convex mixed integer nonlinear programs
Pierre Bonami, Lorenz T. Biegler, Andrew R. Conn et al. · Discrete Optimization · 2007 · 885 citations · Full text
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Massachusetts Institute of Technology
Cambridge, United States
10 h-index
23 publications
1.4K citations
Tsinghua University
Beijing, China
9 h-index
19 publications
1.2K citations
Nanyang Technological University
Singapore, Singapore
6 h-index
6 publications
378 citations

Beijing University of Posts and Telecommunications
Beijing, China
6 h-index
20 publications
854 citations

UNSW Sydney
Sydney, Australia
6 h-index
8 publications
801 citations
Universidad Distrital Francisco José de Caldas
Bogotá, Colombia
6 h-index
7 publications
137 citations

Imperial College London
London, United Kingdom
6 h-index
15 publications
2K citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
10 publications
4.6K citations
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10 publications · 725 citations
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10 publications · 2.6K citations
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9 publications · 521 citations
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8 publications · 879 citations
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7 publications · 308 citations
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