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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Vydáno v:Journal of combinatorial optimization Ročník 32; číslo 2; s. 531 - 549
Hlavní autoři: Wang, Yang, Hao, Jin-Kao, Glover, Fred, Lü, Zhipeng, Wu, Qinghua
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.08.2016
Springer Verlag
Témata:
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
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Shrnutí: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