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Monte Carlo bounding techniques for determining solution quality in stochastic programs

Author
MAK, W.-K1 ; MORTON, D. P2 ; WOOD, R. K3
[1] Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, United States
[2] Graduate Program in Operations Research, The University of Texas at Austin, Austin, TX 78712, United States
[3] Operations Research Department, Naval Postgraduate School, Monterey, CA 93943, United States
Source

Operations research letters. 1999, Vol 24, Num 1-2, pp 47-56 ; ref : 36 ref

CODEN
ORLED5
ISSN
0167-6377
Scientific domain
Control theory, operational research
Publisher
Elsevier, Amsterdam
Publication country
Netherlands
Document type
Article
Language
English
Keyword (fr)
Borne inférieure Echantillonnage Intervalle confiance Programmation stochastique Réduction Statistique Variance Approximation Monte Carlo
Keyword (en)
Lower bound Sampling Confidence interval Stochastic programming Reduction Statistics Variance
Keyword (es)
Cota inferior Muestreo Intervalo confianza Programación estocástica Reducción Estadística Variancia
Classification
Pascal
001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02B Mathematical foundations

Discipline
Mathematics
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
1892746

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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