On a New Collection of Stochastic Linear Programming Test Problems
| Autor: | Andrew J. Felt, K. A. Ariyawansa |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Theoretical computer science
Information retrieval Linear programming Computer science media_common.quotation_subject General Engineering Stochastic programming Test (assessment) Documentation Reading (process) Stochastic optimization Stochastic linear programming Analysis of algorithms media_common |
| Zdroj: | INFORMS Journal on Computing. 16:291-299 |
| ISSN: | 1526-5528 1091-9856 |
| DOI: | 10.1287/ijoc.1030.0037 |
| Popis: | The purpose of this paper is to introduce a new test-problem collection for stochastic linear programming that the authors have recently begun to assemble. While there are existing stochastic programming test-problem collections, our new collection has three features that distinguish it from existing collections. First, our collection is web-based with free public access, and we intend to enrich it as new test problems become available. Indeed, we encourage submissions of new test problems. Second, along with the collection we provide documentation of the problems, so that researchers can quickly find information about each family without reading through the original source. Third, all of the data in our collection are provided in SMPS (Birge et al. 1987, Gassmann and Schweitzer 2001) format. In this paper, we provide an introduction to the stochastic linear program, give a brief description of each problem family currently in the test-problem collection, and describe the documentation that accompanies the collection. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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