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Corpus ID: 2494628

Improving the LP bound of a MILP by branching concurrently

@article{Buesching2007ImprovingTL,
title={Improving the LP bound of a MILP by branching concurrently},
author={H. Georg Buesching},
journal={ArXiv},
year={2007},
volume={abs/0711.0311}
}

We'll measure the differences of the dual variables and the gain of the objective function when creating new problems, which each has one inequality more than the starting LP-instance. These differences of the dual variables are naturally connected to the branches. Then we'll choose those differences of dual variables, so that for all combinations of choices at the connected branches, all dual inequalities will hold for sure. By adding the gain of each chosen branching, we get a total gain… Expand

The outcome is that FP, in spite of its simple foundation, proves competitive with ILOG-Cplex both in terms of speed and quality of the first solution delivered.Expand

Handbook of Approximation Algorithms and Metaheuristics

2007

TLDR

The function ∑n i=1 cixi is known as the objective function, and the m inequalities are known as constraints; the coefficient matrix of the linear program is the m× n matrix A whose entries are aji.Expand