Rounding and Propagation Heuristics for Mixed Integer Programming-Reference-Cited by-同舟云学术

Rounding and Propagation Heuristics for Mixed Integer Programming

Published:2012 Issue: Volume: Page:71-76
ISSN:0721-5924
Container-title:Operations Research Proceedings
language:
Short-container-title:

Author:

Achterberg Tobias,Berthold Timo,Hendel Gregor

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-29210-1_12.pdf

Reference6 articles.

1. T. Achterberg. Constraint Integer Programming. PhD thesis, Technische Universität Berlin, 2007.

2. T. Achterberg, T. Berthold, and G. Hendel. Rounding and propagation heuristics for mixed integer programming. ZIB-Report 11-29, Zuse Institute Berlin, 2011. http://vs24.kobv.de/opus4-zib/frontdoor/index/index/docId/1325/ .

3. T. Berthold. Primal Heuristics for Mixed Integer Programs. Master’s thesis, Technische Universität Berlin, 2006.

4. G. Hendel. New rounding and propagation heuristics for mixed integer programming. Bachelor’s thesis, Technische Universität Berlin, 2011.

5. 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.

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. One-Shot Learning for MIPs with SOS1 Constraints;Operations Research Forum;2024-07-01

2. Routing one million customers in a handful of minutes;Computers & Operations Research;2024-04

3. Local Branching Relaxation Heuristics for Integer Linear Programs;Integration of Constraint Programming, Artificial Intelligence, and Operations Research;2023

4. Improving Primal Heuristics for Mixed Integer Programming Problems based on Problem Reduction: A Learning-based Approach;2022 17th International Conference on Control, Automation, Robotics and Vision (ICARCV);2022-12-11

5. Guidelines for the computational testing of machine learning approaches to vehicle routing problems;Operations Research Letters;2022-03