Scenario grouping in a progressive hedging-based meta-heuristic for stochastic network design

We propose a methodological approach to build strategies for grouping scenarios as defined by the type of scenario decomposition, type of grouping, and the measures specifying scenario similarity. We evaluate these strategies in the context of stochastic network design by analyzing the behavior and...

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Vydáno v:	Computers & operations research Ročník 43; s. 90 - 99
Hlavní autoři:	Crainic, Teodor Gabriel, Hewitt, Mike, Rei, Walter
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.03.2014 Elsevier Pergamon Press Inc
Témata:	Applied sciences Commodities Exact sciences and technology Flows in networks. Combinatorial problems Heuristic Heuristic methods Integer programming Machine learning Mathematical models Mathematical problems Network design Network topologies Networks Operational research and scientific management Operational research. Management science Operations research Progressive hedging Scenario clustering Similarity Stochastic models Stochastic programs Stochasticity Strategy Studies Stochastic programs Network design Progressive hedging Scenario clustering Machine learning Lower bound Script Warranty Similarity Mixed integer programming Grouping Raw materials Stochastic programming Learning (artificial intelligence) Classification Heuristic method Metamodel
ISSN:	0305-0548, 1873-765X, 0305-0548
On-line přístup:	Získat plný text
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