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Large-scale linear optimization
| Content Provider | Scilit |
|---|---|
| Author | Sierksma, Gerard Zwols, Yori |
| Copyright Year | 2015 |
| Description | Overview Although Dantzig's simplex algorithm has proven to be very successful in solving LOmodels of practical problems, its theoretical worst-case behavior is nevertheless very bad. In 1972, Victor Klee (1925-2007) and George J. Minty (1929-1986) constructed examples for which the simplex algorithm requires an exorbitant amount of computer running time; see Chapter 9. The reason that the simplex algorithm works fast in practice is that LOmodels arising from most practical problems are usually so-called 'average' problems and are fortunately not the rare 'worst-case' problems. Besides the theoretical question whether or not there exists a fast algorithm that solves large-scale linear optimization problems, also the practical need for such an ecient algorithm has inspired researchers to try to answer this question. Book Name: Linear and Integer Optimization |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2016-0-24318-0&isbn=9780429159961&doi=10.1201/b18378-11&format=pdf |
| Ending Page | 308 |
| Page Count | 32 |
| Starting Page | 277 |
| DOI | 10.1201/b18378-11 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2015-05-01 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Linear and Integer Optimization Operations Research and Management Science Simplex Algorithm Linear Optimization Practical Problems Scale Linear |
| Content Type | Text |
| Resource Type | Chapter |
