Computational tractability of chance constrained data envelopment analysis
• Distributionally robust chance constrained data envelopment analysis is discussed. • Correlation assumption in chance constrained data envelopment analysis is relaxed. • Models can be reformulated as conic programming problems. • Satisficing model is nonconvex under Gaussian assumption. • Satisfic...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Chen, Kun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Umfang: |
10 |
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| Übergeordnetes Werk: |
Enthalten in: Valorization of fatty acid waste for bioplastics production using Bacillus tequilensis: Integration with dark-fermentative hydrogen production process - Venkateswar Reddy, M. ELSEVIER, 2014transfer abstract, EJOR, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:274 ; year:2019 ; number:3 ; day:1 ; month:05 ; pages:1037-1046 ; extent:10 |
| Links: |
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| DOI / URN: |
10.1016/j.ejor.2018.10.039 |
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ELV045336873 |
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| 520 | |a • Distributionally robust chance constrained data envelopment analysis is discussed. • Correlation assumption in chance constrained data envelopment analysis is relaxed. • Models can be reformulated as conic programming problems. • Satisficing model is nonconvex under Gaussian assumption. • Satisficing model is quasi-convex under distributionally robust assumption. | ||
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• Distributionally robust chance constrained data envelopment analysis is discussed. • Correlation assumption in chance constrained data envelopment analysis is relaxed. • Models can be reformulated as conic programming problems. • Satisficing model is nonconvex under Gaussian assumption. • Satisficing model is quasi-convex under distributionally robust assumption. |
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• Distributionally robust chance constrained data envelopment analysis is discussed. • Correlation assumption in chance constrained data envelopment analysis is relaxed. • Models can be reformulated as conic programming problems. • Satisficing model is nonconvex under Gaussian assumption. • Satisficing model is quasi-convex under distributionally robust assumption. |
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