Solving the maximum vertex weight clique problem via binary quadratic programming

In recent years, the general binary quadratic programming (BQP) model has been widely applied to solve a number of combinatorial optimization problems. In this paper, we recast the maximum vertex weight clique problem (MVWCP) into this model which is then solved by a probabilistic tabu search algori...

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Bibliographic Details
Published in:Journal of combinatorial optimization Vol. 32; no. 2; pp. 531 - 549
Main Authors: Wang, Yang, Hao, Jin-Kao, Glover, Fred, Lü, Zhipeng, Wu, Qinghua
Format: Journal Article
Language:English
Published: New York Springer US 01.08.2016
Springer Verlag
Subjects:
Combinatorics
Computer Science
Convex and Discrete Geometry
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Theory of Computation
Maximum vertex weight clique
Binary quadratic programming
Probabilistic tabu search
ISSN:1382-6905, 1573-2886
Online Access:Get full text
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Summary:In recent years, the general binary quadratic programming (BQP) model has been widely applied to solve a number of combinatorial optimization problems. In this paper, we recast the maximum vertex weight clique problem (MVWCP) into this model which is then solved by a probabilistic tabu search algorithm designed for the BQP. Experimental results on 80 challenging DIMACS-W and 40 BHOSLIB-W benchmark instances demonstrate that this general approach is viable for solving the MVWCP problem.
ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-016-9990-2