Reformulation-Linearization Technique for MIPs
Published Online: 15 FEB 2011
Copyright © 2010 John Wiley & Sons, Inc. All rights reserved.
Wiley Encyclopedia of Operations Research and Management Science
How to Cite
Sherali, H. D. 2011. Reformulation-Linearization Technique for MIPs. Wiley Encyclopedia of Operations Research and Management Science. .
- Published Online: 15 FEB 2011
The reformulation-linearization technique (RLT) for mixed-integer programs is an automatic model enhancement approach that generates a hierarchy of relaxations spanning the spectrum from the continuous linear programming (LP) relaxation to the convex hull of feasible solutions. This process is applicable to both 0-1 as well as general discrete programs, and can be further augmented through the use of classes of semidefinite cuts. Often, the first-level relaxation itself provides a sufficiently tight model reformulation that significantly improves problem solvability. The RLT procedure also offers a unifying framework for solving continuous nonconvex factorable optimization problems to global optimality.
- reformulation-linearization technique;
- mixed-integer programming;
- tight relaxations;
- valid inequalities;
- model reformulation;
- convex hull;
- nonconvex programs;
- global optimization