A branch and bound method for stochastic global optimization

DOI10.1007/BF02680569zbMath0920.90111OpenAlexW2017411673WikidataQ89282731 ScholiaQ89282731MaRDI QIDQ1290672

Vladimir I. Norkin, Ruszczyński, Andrzej, Georg Ch. Pflug

Publication date: 3 June 1999

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02680569

zbMATH Keywords

convergence stochastic global optimization facility location stochastic branch-and-bound method

Mathematics Subject Classification ID

Stochastic programming (90C15) Discrete location and assignment (90B80)

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Cites Work