506. Improving the Semi-Lagrangian Relaxation Approach to the Simple Plant Location Problem
Invited abstract in session MC-15: Relaxation and Decomposition, stream Combinatorial Optimization.
Monday, 12:30-14:00Room: Esther Simpson 1.08
Authors (first author is the speaker)
| 1. | Lauren Durrell
|
| Mathematics, Lancaster University | |
| 2. | THU HUONG DANG
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| Mathematics and Statistics, Management Science, Lancaster University | |
| 3. | Adam Letchford
|
| Department of Management Science, Lancaster University |
Abstract
The Simple Plant Location Problem (SPLP) is a much-studied combinatorial optimisation problem with many applications. In 2012, Beltran-Royo et al. devised an intriguing exact algorithm for the SPLP, based on semi-Lagrangian relaxation. We show that one can speed up that algorithm considerably by (a) using a fast method to initialise the Lagrangian multipliers, and (b) eliminating redundant variables from the relaxed problem. The enhanced algorithm performs extremely well on several hard benchmark instances.
Keywords
- Combinatorial Optimization
- Location
Status: accepted
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