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Computational Management Science : CMS
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Coping with uncertainty : modeling and policy issues
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Dynamic stochastic optimization : [this volume includes a selection of papers presented at the IFIP/IIASA/GAMM-Workshop on "Dynamic Stochastic Optimization" held at the International Institute for Systems Analysis (IIASA), Laxenburg, Austria, March 11 - 14, 2002]/ Kurt Marti ... (eds.)
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B&B method for discrete partial order optimization
Norkin, Vladimir I.
- In:
Computational Management Science : CMS
16
(
2019
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4
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pp. 577-592
Persistent link: https://www.econbiz.de/10012126679
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Stochastic optimization of risk functions via parametric smoothing
Ermolʹev, Jurij M.
;
Norkin, Vladimir I.
- In:
Dynamic stochastic optimization : [this volume includes …
,
(pp. 225-247)
.
2004
Persistent link: https://www.econbiz.de/10003488010
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On optimal allocation of indivisibles under uncertainty
Norkin, Vladimir I.
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Ermolʹev, Jurij M.
;
Ruszczyński, …
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1994
Persistent link: https://www.econbiz.de/10000914904
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Endogenous risks and learning in climate change decision analysis
O'Neill, Brian C.
;
Ermolʹev, Jurij M.
;
Ermol'eva, …
- In:
Coping with uncertainty : modeling and policy issues
,
(pp. 283-300)
.
2006
Persistent link: https://www.econbiz.de/10003394897
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Energy efficiency and risk management in public buildings : strategic model for robust planning
Cano, Emilio L.
;
Moguerza, Javier M.
;
Ermol'eva, Tatiana Y.
- In:
Computational Management Science : CMS
11
(
2014
)
1/2
,
pp. 25-44
Persistent link: https://www.econbiz.de/10010251214
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