Presolving in linear programming
Mathematical Programming: Series A and B
Computational Combinatorial Optimization, Optimal or Provably Near-Optimal Solutions [based on a Spring School]
Branch-and-Bound Algorithms for the Test Cover Problem
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
| Hi-index | 0.00 |
The test-cover problem asks for the minimal number of tests needed to uniquely identify a disease, infection, etc. A collection of branch-and-bound algorithms was proposed by De Bontridder et al. [2002]. Based on their work, we introduce several improvements that are compatible with all techniques described in De Bontridder et al. [2002] and the more general setting of weighted test-cover problems. We present a faster data structure, cost-based variable fixing, and adapt well-known set-covering techniques, including Lagrangian relaxation and upper-bound heuristics. The resulting algorithm solves benchmark instances up to 10 times faster than the former approach and up to 100 times faster than a general MIP solver.