SCIL -- symbolic constraints in integer linear programming We describe a new software system SCIL that introduces symbolic constraints into branch-and-cut-and-price algorithms for integer linear programs. Symbolic constraints are known from constraint programming and contribute significantly to the expressive power, ease of use, and efficiency of constraint programming systems.
Keywords for this software
References in zbMATH (referenced in 9 articles , 1 standard article )
Showing results 1 to 9 of 9.
- Salvagnin, Domenico: Detecting semantic groups in MIP models (2016)
- Cymer, Radosław: Gallai-Edmonds decomposition as a pruning technique (2015)
- Buchheim, Christoph; Klein, Laura: Combinatorial optimization with one quadratic term: spanning trees and forests (2014)
- Benchimol, Pascal; van Hoeve, Willem-Jan; Régin, Jean-Charles; Rousseau, Louis-Martin; Rueher, Michel: Improved filtering for weighted circuit constraints (2012)
- Achterberg, Tobias: SCIP: solving constraint integer programs (2009)
- Achterberg, Tobias; Berthold, Timo; Koch, Thorsten; Wolter, Kati: Constraint integer programming: A new approach to integrate CP and MIP (2008)
- Althaus, E.; Călinescu, G.; Măndoiu, I.I.; Prasad, S.; Tchervenski, N.; Zelikovsky, A.: Power efficient range assignment for symmetric connectivity in static ad hoc wireless networks (2006) ioport
- Althaus, Ernst; Caprara, Alberto; Lenhof, Hans-Peter; Reinert, Knut: A branch-and-cut algorithm for multiple sequence alignment (2006)
- Althaus, Ernst; Bockmayr, Alexander; Elf, Matthias; Jünger, Michael; Kasper, Thomas; Mehlhorn, Kurt: SCIL -- symbolic constraints in integer linear programming (2002)