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  • Convergence  (1)
  • Key words: probabilistic programming – discrete distributions – generalized concavity – column generation Mathematics Subject Classification (1991): 90C15, 90C11, 65K05, 49M27  (1)
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  • 1
    Digitale Medien
    Digitale Medien
    Feasible direction methods for stochastic programming problems (1980)
    Springer
    Mathematical programming 19 (1980), S. 220-229 
    Details
    ISSN: 1436-4646
    Schlagwort(e): Stochastic Programming ; Feasible Direction Methods ; Point-to-Set Maps ; Convergence
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Informatik , Mathematik
    Notizen: Abstract A unified approach to stochastic feasible direction methods is developed. An abstract point-to-set map description of the algorithm is used and a general convergence theorem is proved. The theory is used to develop stochastic analogs of classical feasible direction algorithms.
    Materialart: Digitale Medien
    URL: http://dx.doi.org/10.1007/BF01581643
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Digitale Medien
    Digitale Medien
    Concavity and efficient points of discrete distributions in probabilistic programming (2000)
    Springer
    Mathematical programming 89 (2000), S. 55-77 
    Details
    ISSN: 1436-4646
    Schlagwort(e): Key words: probabilistic programming – discrete distributions – generalized concavity – column generation Mathematics Subject Classification (1991): 90C15, 90C11, 65K05, 49M27
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Informatik , Mathematik
    Notizen: Abstract. We consider stochastic programming problems with probabilistic constraints involving integer-valued random variables. The concept of a p-efficient point of a probability distribution is used to derive various equivalent problem formulations. Next we introduce the concept of r-concave discrete probability distributions and analyse its relevance for problems under consideration. These notions are used to derive lower and upper bounds for the optimal value of probabilistically constrained stochastic programming problems with discrete random variables. The results are illustrated with numerical examples.
    Materialart: Digitale Medien
    URL: http://dx.doi.org/10.1007/PL00011393
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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    Artikel (Nationallizenzen)
    Volltext
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