On capacity expansion planning under strategic and operational uncertainties based on stochastic dominance risk averse management

On capacity expansion planning under strategic and operational uncertainties based on stochastic... Comput Manag Sci https://doi.org/10.1007/s10287-018-0318-9 ORIGINAL PAPER On capacity expansion planning under strategic and operational uncertainties based on stochastic dominance risk averse management 1 2 Laureano F. Escudero · Juan F. Monge Received: 27 September 2017 / Accepted: 22 May 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract A new scheme for dealing with uncertainty in scenario trees is presented for dynamic mixed 0–1 optimization problems with strategic and operational stochastic parameters. Let us generically name this type of problems as capacity expansion plan- ning (CEP) in a given system, e.g., supply chain, production, rapid transit network, energy generation and transmission network, etc. The strategic scenario tree is usually a multistage one, and the replicas of the strategic nodes root structures in the form of either a special scenario graph or a two-stage scenario tree, depending on the type of operational activity in the system. Those operational scenario structures impact in the constraints of the model and, thus, in the decomposition methodology for solving usu- ally large-scale problems. This work presents the modeling framework for some of the risk neutral and risk averse measures to consider for CEP problem solving. Two types of risk averse measures are http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computational Management Science Springer Journals

On capacity expansion planning under strategic and operational uncertainties based on stochastic dominance risk averse management

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Business and Management; Operations Research/Decision Theory; Optimization
ISSN
1619-697X
eISSN
1619-6988
D.O.I.
10.1007/s10287-018-0318-9
Publisher site
See Article on Publisher Site

Abstract

Comput Manag Sci https://doi.org/10.1007/s10287-018-0318-9 ORIGINAL PAPER On capacity expansion planning under strategic and operational uncertainties based on stochastic dominance risk averse management 1 2 Laureano F. Escudero · Juan F. Monge Received: 27 September 2017 / Accepted: 22 May 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract A new scheme for dealing with uncertainty in scenario trees is presented for dynamic mixed 0–1 optimization problems with strategic and operational stochastic parameters. Let us generically name this type of problems as capacity expansion plan- ning (CEP) in a given system, e.g., supply chain, production, rapid transit network, energy generation and transmission network, etc. The strategic scenario tree is usually a multistage one, and the replicas of the strategic nodes root structures in the form of either a special scenario graph or a two-stage scenario tree, depending on the type of operational activity in the system. Those operational scenario structures impact in the constraints of the model and, thus, in the decomposition methodology for solving usu- ally large-scale problems. This work presents the modeling framework for some of the risk neutral and risk averse measures to consider for CEP problem solving. Two types of risk averse measures are

Journal

Computational Management ScienceSpringer Journals

Published: May 30, 2018

References

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