Notice bibliographique
- Notice
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001 FRBNF447160680000008
010 .. $a 9783834899910
035 .. $a OCoLC455487722
100 .. $a 20170801d2009 m y0engy50 ba
101 0. $a eng
102 .. $a DE
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106 .. $a s $a z
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181 .0 $6 01 $a i $b xxxe
181 .. $6 02 $c txt $2 rdacontent
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182 .. $6 02 $c c $2 rdamedia
200 1. $a Decision making with dominance constraints in two-stage stochastic integer programming $b Texte électronique $f Uwe Gotzes $g with a foreword by Rüdiger Schultz
205 .. $a 1. Aufl
210 .. $a Wiesbaden $c Vieweg+Teubner Research $d cop. 2009
215 .. $a 1 online resource (89 pages)
225 1. $a Vieweg+Teubner research. Stochastic programming
300 .. $a Includes bibliographical references and index
300 .. $a Print version record.
330 .. $a Two-stage stochastic programming models are considered as attractive tools for making
optimal decisions under uncertainty. Traditionally, optimality is formalized by applying
statistical parameters such as the expectation or the conditional value at risk to
the distributions of objective values. Uwe Gotzes analyzes an approach to account
for risk aversion in two-stage models based upon partial orders on the set of real
random variables. These stochastic orders enable the incorporation of the characteristics
of whole distributions into the decision process. The profit or cost distributions
must pass a benchmark test with a given acceptable distribution. Thus, additional
objectives can be optimized. For this new class of stochastic optimization problems,
results on structure and stability are proven and a tailored algorithm to tackle large
problem instances is developed. The implications of the modelling background and numerical
results from the application of the proposed algorithm are demonstrated with case
studies from energy trading
676 .. $a 510 $v 23
801 .3 $a US $b OCoLC $c 20170801 $h 455487722 $2 marc21
801 .0 $b CUS $g pn
930 .. $5 FR-759999999:44716068001001 $a ACQNUM-97834 $b 759999999 $c Document numérisé $d N
