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Affine recourse for the robust network design problem: Between static and dynamic routing

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TLDR
It is shown that affine routing can be seen as a generalization of the widely used static routing while still being tractable and providing cheaper solutions and that for these instances the optimal solutions based on affine routings tend to be as cheap as optimal network designs for dynamic routings.
Abstract
Affinely Adjustable Robust Counterparts provide tractable alternatives to (two-stage) robust programs with arbitrary recourse. Following Ouorou and Vial, we apply them to robust network design with polyhedral demand uncertainty, introducing the notion of affine routing. We compare the new affine routing scheme to the well-studied static and dynamic routing schemes for robust network design. It is shown that affine routing can be seen as a generalization of the widely used static routing while still being tractable and providing cheaper solutions. We investigate properties of the demand polytope under which affine routings reduce to static routings and also develop conditions on the uncertainty set leading to dynamic routings being affine. We show however that affine routings suffer from the drawback that (even totally) dominated demand vectors are not necessarily supported by affine solutions. Uncertainty sets have to be designed accordingly. Finally, we present computational results on networks from SNDlib. We conclude that for these instances the optimal solutions based on affine routings tend to be as cheap as optimal network designs for dynamic routings. In this respect the affine routing principle can be used to approximate the cost for two-stage solutions with free recourse which are hard to compute

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Citations
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Journal ArticleDOI

Collaborative distribution network design with surging demand and facility disruptions

TL;DR: In this paper , a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is proposed, where a tailored column-and-constraint generation algorithm is utilized to solve the proposed robust model.
References
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Journal ArticleDOI

The Price of Robustness

TL;DR: In this paper, the authors propose an approach that attempts to make this trade-off more attractive by flexibly adjusting the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations.

The price of the robustness

D Bertsimas, +1 more
TL;DR: An approach is proposed that flexibly adjust the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations, and an attractive aspect of this method is that the new robust formulation is also a linear optimization problem, so it naturally extend to discrete optimization problems in a tractable way.
Journal ArticleDOI

Partitioning procedures for solving mixed-variables programming problems

TL;DR: In this article, the 8th International Meeting of the Institute of Management Sciences, Brussels, August 23-26, 1961, the authors presented a paper entitled "The International Journal of Management Science and Management Sciences".
Journal ArticleDOI

Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming

TL;DR: This note formulates a convex mathematical programming problem in which the usual definition of the feasible region is replaced by a significantly different strategy via set containment.
Journal ArticleDOI

Robust solutions of uncertain linear programs

TL;DR: It is shown that the RC of an LP with ellipsoidal uncertainty set is computationally tractable, since it leads to a conic quadratic program, which can be solved in polynomial time.
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