Name
Abstract | ||
|---|---|---|
Industrial optimization applications must be "robust," i.e., must provide good solutions to problem instances of different size and numerical characteristics, and continue to work well when side constraints are added. This paper presents a case study in which this requirement and its consequences on the applicability of different optimization techniques have been addressed. An extensive benchmark suite, built on real network design data provided by France Telecom R&D, has been used to test multiple algorithms for robustness against variations in problem size, numerical characteristics, and side constraints. The experimental results illustrate the performance discrepancies that have occurred and how some have been corrected. In the end, the results suggest that we shall remain very humble when assessing the adequacy of a given algorithm for a given problem, and that a new generation of public optimization benchmark suites is needed for the academic community to attack the issue of algorithm robustness as it is encountered in industrial settings. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-46135-3_42 | CP |
Keywords | Field | DocType |
network design problem,problem size,public optimization benchmark suite,side constraint,problem instance,different optimization technique,algorithm robustness,different size,numerical characteristic,extensive benchmark suite,industrial optimization application,network design | Algorithm robustness,Mathematical optimization,Telecommunications network,Suite,Network planning and design,Computer science,Cryptanalysis,Robustness (computer science),Integer programming,Academic community | Conference |
ISBN | Citations | PageRank |
3-540-44120-4 | 11 | 0.95 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claude Le Pape | 1 | 481 | 52.87 |
| Laurent Perron | 2 | 240 | 53.16 |
| Jean-charles Régin | 3 | 1312 | 96.59 |
| Paul Shaw | 4 | 81 | 5.73 |