Abstract
In this paper, we present several primal heuristics which we implemented in the branch-and-price solver GCG based on the SCIP framework. This involves new heuristics as well as heuristics from the literature that make use of the reformulation yielded by the Dantzig-Wolfe decomposition. We give short descriptions of those heuristics and briefly discuss computational results. Furthermore, we give an outlook on current and further development.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Achterberg, T.: SCIP: Solving constraint integer programs. Mathematical Programming Computation 1(1), 1–41 (2009). http://mpc.zib.de/index.php/MPC/article/view/4
Achterberg, T., Koch, T.,Martin, A.: MIPLIB 2003. Operations Research Letters 34(4), 361–372 (2006). http://miplib.zib.de
Bergner, M., Caprara, A., Furini, F., LÜbbecke, M.,Malaguti, E., Traversi, E.: Partial convexification of general MIPs by Dantzig-Wolfe reformulation. In: GÜnlÜk, O., Woeginger, G.J. (eds.), Integer Programming and Combinatorial Optimization (IPCO 2011), LNCS, 6655, pp. 39-51. Springer, Berlin (2011)
Berthold, T.: Primal Heuristics for Mixed Integer Programs. Master’s thesis. Technische Universität Berlin (2006)
Dantzig, G.B.,Wolfe, P.: Decomposition Principle for Linear Programs. Operations Research 8(1), 101–111 (1960)
Desrosiers, J., LÜbbecke, M.: A Primer in Column Generation. In: Desaulniers, G., Desrosiers, J., Solomon, M.M. (eds.), Column Generation, pp. 1-32. Springer, US (2005)
Fischetti, M., Glover, F., Lodi, A.: The feasibility pump. Mathematical Programming 104, 91–104 (2005)
Gamrath, G., LÜbbecke, M.: Experiments with a Generic Dantzig-Wolfe Decomposition for Integer Programs. In: Festa, P. (ed.), Experimental Algorithms, LNCS, 6049, pp. 239-252. Springer, Berlin (2010)
Joncour, C., Michel, S., Sadykov, R., Sverdlov, D., and Vanderbeck, F.: Column Generation based Primal Heuristics. Electronic Notes in Discrete Mathematics 3, 695–702 (2010). ISCO 2010 – International Symposium on Combinatorial Optimization.
T. Koch, T. Achterberg, E. Andersen, O. Bastert, T. Berthold, R. E. Bixby, E. Danna, G. Gamrath, A. M. Gleixner, S. Heinz, A. Lodi, H. Mittelmann, T. Ralphs, D. Salvagnin, D. E. Steffy, and K. Wolter. MIPLIB 2010. Mathematical Programming Computation, 3(2):103–163, 2011.
Puchert, C.: Primal Heuristics for Branch-and-Price Algorithms. Master’s thesis. Technische Universität Darmstadt (2011)
Rothberg, E.: An Evolutionary Algorithm for Polishing Mixed Integer Programming Solutions. ILOG Inc. (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lübbecke, M., Puchert, C. (2012). Primal Heuristics for Branch-and-Price Algorithms. In: Klatte, D., Lüthi, HJ., Schmedders, K. (eds) Operations Research Proceedings 2011. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29210-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-29210-1_11
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29209-5
Online ISBN: 978-3-642-29210-1
eBook Packages: Business and EconomicsBusiness and Management (R0)