1092. On strengthening some mixed integer optimization algorithms via additional improving steps
Invited abstract in session WB-17: Integer Programming, stream Combinatorial Optimization.
Wednesday, 10:30-12:00Room: Esther Simpson 2.08
Authors (first author is the speaker)
| 1. | Monique Guignard-Spielberg
|
| OID, University of Pennsylvania |
Abstract
Several strengthening tools can be used as intermediate steps for obtaining improved algorithmic performance in the solution of optimization problems in 0-1 variables. This talk will concentrate on a few such tools, based, respectively or simultaneously, on the RLT (i.e., Reformulation Linearization Technique) of Adams and Sherali, Lagrangean relaxation, pioneered by Geoffrion in 1975 in Management Science, the ILP (Integer Linearization Property) of Geoffrion (1974), Geoffrion and Mc Bride (1978) and Guignard-Spielberg (2003), and, in the case of linear constraints and quadratic objective function, decomposable Lagrangean Relaxation or Decomposition (Guignard 2020).
After reviewing these tools, several instances and respective numerical results will be presented, for instances with nonlinear objective function and linear constraints.
Keywords
- Combinatorial Optimization
- Algorithms
- Programming, Mixed-Integer
Status: accepted
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