Results 91 to 100 of about 145 (122)
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Polyhedral Combinatorics of Benzenoid Problems
Lecture Notes in Computer Science, 1998Many chemical properties of benzenoid hydrocarbons can be understood in terms of the maximum number of mutually resonant hexagons, or Clar number, of the molecules. Hansen and Zheng (1994) formulated this problem as an integer program and conjectured, based on computational evidence, that solving the linear programming relaxation always yields integral
Gary Atkinson
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Polyhedral Combinatorics in Combinatorial Optimization
Statistica Neerlandica, 1987Polyhedral combinatorics is a subarea of combinatorial optimization of increasing practical importance. It deals with the application of the theory of linear systems and linear algebra to combinatorial problems. The paper is not intended as a survey on polyhedral combinatorics but it reviews some of the main concepts and proof techniques.
Gerards, A.M.H., Kolen, A.W.J.
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Journal of Combinatorial Optimization, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vicky Mak, Tommy Thomadsen
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vicky Mak, Tommy Thomadsen
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Polyhedral Combinatorics of Quadratic Assignment Problems with Less Objects than Locations
Lecture Notes in Computer Science, 1998For the classical quadratic assignment problem (QAP) that requires n objects to be assigned to n locations (the n × n-case), polyhe- dral studies have been started in the very recent years by several authors. In this paper, we investigate the variant of the QAP, where the number of locations may exceed the number of objects (the m × n-case).
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Chapter V Polyhedral combinatorics
Handbooks in Operations Research and Management Science, 1989W R Pulleyblank
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D.R. Fulkerson’s contributions to polyhedral combinatorics
Mathematical Programming Studies, 1978Hoffman A J
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Polyhedral combinatorics and the acyclic subdigraph problem
Mathematical Social Sciences, 1986F W Roush
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Polyhedral Combinatorics and Neural Networks
Neural Computation, 1994The often disappointing performance of optimizing neural networks can be partly attributed to the rather ad hoc manner in which problems are mapped onto them for solution. In this paper a rigorous mapping is described for quadratic 0-1 programming problems with linear equality and inequality constraints, this being the most general class of problem ...
Andrew H. Gee, Richard W. Prager
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