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Hybrid branching combines all four selection criteria into a single one and additionally includes a score which is based on the number of subproblems that could be pruned due to branching on this variable, called the cutoff values.
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In this paper, we present hybrid branching, which combines selection rules from all three fields. Download to read the full chapter text.
Pseudocost branching. > try to estimate LP values, based on history information. > effective, cheap, but weak in the beginning.
The question how to split a problem into subproblems (branching) is in the core of any branch-and-bound algorithm. Branching on individual variables is very ...
A recent Graph Neural Network (GNN) approach for learning to branch has been shown to successfully reduce the running time of branch-and-bound (B&B).
This paper presents hybrid branching, which combines selection rules from all three fields, and shows how branching on individual variables in CSP, MIP, ...
The question how to split a problem into subproblems <em>(branching)</em> is in the core of any branch-and-bound algorithm. Branching on individual variables is ...
Jun 9, 2023 · Abstract:Cutting planes and branching are two of the most important algorithms for solving mixed-integer linear programs.
Hybrid branching-time logics are a powerful extension of branching-time logics like CTL, CTL∗ or even the modal µ-calculus through the addition of binders ...
We consider hybridisations of the full branching time logic ⁎ and its prominent fragments CTL, and through the addition of nominals, binders and jumps.