Abstract
We describe new algorithms for solving linear programming relaxations of very large precedence constrained production scheduling problems. We present theory that motivates a new set of algorithmic ideas that can be employed on a wide range of problems; on data sets arising in the mining industry our algorithms prove effective on problems with many millions of variables and constraints, obtaining provably optimal solutions in a few minutes of computation. © 2010 Springer-Verlag.
Cite
CITATION STYLE
Bienstock, D., & Zuckerberg, M. (2010). Solving LP relaxations of large-scale precedence constrained problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6080 LNCS, pp. 1–14). https://doi.org/10.1007/978-3-642-13036-6_1
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