Stochastic Network Design

Mike Hewitt (), Walter Rei () and Stein Wallace
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Mike Hewitt: Loyola University Chicago
Walter Rei: Université du Québec à Montréal

Chapter Chapter 10 in Network Design with Applications to Transportation and Logistics, 2021, pp 283-315 from Springer

Abstract: Abstract Network design problems often appear in informational contexts that involve both different sources and varying levels of uncertainty. Optimization methods that explicitly account for such uncertainty are thus required to design efficient networks. This chapter focuses on stochastic network design methods, both the main modelling paradigms and the solution procedures that can be applied. The paradigms are first illustrated on a specific problem, namely the stochastic fixed-charge capacitated multicommodity network design problem. This is followed up with a presentation of how scenario generation is applied to approximate the random distributions used to model the stochastic parameters in network design models. The general solution approaches (both exact and heuristics) that can be applied to solve stochastic network design models are then described. This description is centered mainly on how decomposition strategies are used to produce more efficient solution processes for the considered models. Finally, the chapter concludes with some perspectives regarding the future research in the field.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-64018-7_10

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DOI: 10.1007/978-3-030-64018-7_10

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