A scenario generation-based lower bounding approach for stochastic scheduling problems / L. Liao in Journal of the operational research society (JORS), Vol. 63 N° 10 (Octobre 2012)  

Public ISBD [article]  inJournal of the operational research society (JORS) > Vol. 63 N° 10 (Octobre 2012) . - pp. 1410–1420 Titre : A scenario generation-based lower bounding approach for stochastic scheduling problems Type de document : texte imprimé Auteurs : L. Liao, Auteur ; S. C. Sarin, Auteur ; Sherali, H. D., Auteur Année de publication : 2012 Article en page(s) : pp. 1410–1420 Langues : Anglais (eng) Mots-clés : scheduling  stochastic programming  scenario generation  discrete bounding  total weighted tardiness Index. décimale : 001.424 Résumé : In this paper, we investigate scenario generation methods to establish lower bounds on the optimal objective value for stochastic scheduling problems that contain random parameters with continuous distributions. In contrast to the Sample Average Approximation (SAA) approach, which yields probabilistic bound values, we use an alternative bounding method that relies on the ideas of discrete bounding and recursive stratified sampling. Theoretical support is provided for deriving exact lower bounds for both expectation and conditional value-at-risk objectives. We illustrate the use of our method on the single machine total weighted tardiness problem. The results of our numerical investigation demonstrate good properties of our bounding method, compared with the SAA method and an earlier discrete bounding method. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n10/abs/jors2011150a.html [article] A scenario generation-based lower bounding approach for stochastic scheduling problems [texte imprimé] / L. Liao, Auteur ; S. C. Sarin, Auteur ; Sherali, H. D., Auteur . - 2012 . - pp. 1410–1420. Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 63 N° 10 (Octobre 2012) . - pp. 1410–1420 Mots-clés : scheduling  stochastic programming  scenario generation  discrete bounding  total weighted tardiness Index. décimale : 001.424 Résumé : In this paper, we investigate scenario generation methods to establish lower bounds on the optimal objective value for stochastic scheduling problems that contain random parameters with continuous distributions. In contrast to the Sample Average Approximation (SAA) approach, which yields probabilistic bound values, we use an alternative bounding method that relies on the ideas of discrete bounding and recursive stratified sampling. Theoretical support is provided for deriving exact lower bounds for both expectation and conditional value-at-risk objectives. We illustrate the use of our method on the single machine total weighted tardiness problem. The results of our numerical investigation demonstrate good properties of our bounding method, compared with the SAA method and an earlier discrete bounding method. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n10/abs/jors2011150a.html

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