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.
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Bienstock, D., Zuckerberg, M. (2010). Solving LP Relaxations of Large-Scale Precedence Constrained Problems. In: Eisenbrand, F., Shepherd, F.B. (eds) Integer Programming and Combinatorial Optimization. IPCO 2010. Lecture Notes in Computer Science, vol 6080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13036-6_1
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DOI: https://doi.org/10.1007/978-3-642-13036-6_1
Publisher Name: Springer, Berlin, Heidelberg
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