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Continuous cubic formulations for cluster detection problems in networks
- Source :
- Mathematical Programming. 196:279-307
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- The celebrated Motzkin–Straus formulation for the maximum clique problem provides a nontrivial characterization of the clique number of a graph in terms of the maximum value of a nonconvex quadratic function over a standard simplex. It was originally developed as a way of proving Turan’s theorem in graph theory, but was later used to develop competitive algorithms for the maximum clique problem based on continuous optimization. Clique relaxations, such as s-defective clique and s-plex, emerged as attractive, more practical alternatives to cliques in network-based cluster detection models arising in numerous applications. This paper establishes continuous cubic formulations for the maximum s-defective clique problem and the maximum s-plex problem by generalizing the Motzkin–Straus formulation to the corresponding clique relaxations. The formulations are used to extend Turan’s theorem and other known lower bounds on the clique number to the considered clique relaxations. Results of preliminary numerical experiments with the CONOPT solver demonstrate that the proposed formulations can be used to quickly compute high-quality solutions for the maximum s-defective clique problem and the maximum s-plex problem. The proposed formulations can also be used to generate interesting test instances for global optimization solvers.
- Subjects :
- Discrete mathematics
Continuous optimization
021103 operations research
Simplex
General Mathematics
Numerical analysis
0211 other engineering and technologies
Graph theory
010103 numerical & computational mathematics
02 engineering and technology
Quadratic function
Solver
01 natural sciences
Clique problem
Computer Science::Discrete Mathematics
0101 mathematics
Global optimization
Software
MathematicsofComputing_DISCRETEMATHEMATICS
Mathematics
Subjects
Details
- ISSN :
- 14364646 and 00255610
- Volume :
- 196
- Database :
- OpenAIRE
- Journal :
- Mathematical Programming
- Accession number :
- edsair.doi...........9cef754c9b7d0d4a9d8109be234d9104