Name
Abstract | ||
|---|---|---|
Users of linear programming computer codes have realized the necessity of evaluating the capacity, effectiveness, and accuracy of the solutions provided by such codes. Large scale linear programming codes at most installations are assumed to be generating correct solutions without ever having been “bench-marked” by test problems with known solutions. The reason for this failure to adequately test the codes is that rarely are there large problems with known solutions readily available. This paper presents a theoretical justification and an Illustrative implementation of a method for generating linear programming test problems with known solutions. The method permits the generation of test problems that are of arbitrary size and have a wide range of numerical characteristics. |
Year | DOI | Venue |
|---|---|---|
1974 | 10.1145/355620.361173 | Commun. ACM |
Keywords | Field | DocType |
lp program validation,test problem generation,linear programming,lp program evaluation,linear programming test problem,linear programming code,arbitrary size,illustrative implementation,large problem,known solution,correct solution,large scale,linear programming computer code,test problem,linear program,program evaluation | Linear-fractional programming,Mathematical optimization,Computer science,Theoretical computer science,Linear programming | Journal |
Volume | Issue | ISSN |
17 | 10 | 0001-0782 |
Citations | PageRank | References |
6 | 3.91 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Charnes | 1 | 271 | 145.50 |
| W. Raike | 2 | 15 | 7.78 |
| J. D. Stutz | 3 | 6 | 3.91 |
| A. S. Walters | 4 | 6 | 4.59 |