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Open AccessJournal ArticleDOI

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

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

The robust vehicle routing problem with time windows

TL;DR: This paper addresses the robust vehicle routing problem with time windows by proposing two new formulations for the robust problem, each based on a different robust approach, and develops a new cutting plane technique for robust combinatorial optimization problems with complicated constraints.

A cutting plane algorithm for multicomoodity survivable network design problems

Geir Dahl, +1 more
TL;DR: A cutting plane algorithm is presented for solving the following telecommunications network design problem: given point-to-point traffic demands in a network, specified survivability requirements and a discrete cost/capacity function for each link, find minimum cost capacity expansions satisfying the given demands.
Journal ArticleDOI

Robust and Adaptive Network Flows

TL;DR: This paper shows that the robust maximum flow problem can be solved in polynomial time, but the robust minimum cut problem is NP-hard, and proves that the adaptive versions are NP- hard.
Journal ArticleDOI

Decomposition for adjustable robust linear optimization subject to uncertainty polytope

TL;DR: A general decomposition framework to solve exactly adjustable robust linear optimization problems subject to polytope uncertainty and shows that the relative performance of the algorithms depend on whether the budget is integer or fractional.
Journal ArticleDOI

A copositive approach for two-stage adjustable robust optimization with uncertain right-hand sides

TL;DR: In this article, the affine policy is reformulated as a copositive optimization problem, which leads to a class of tractable, semidefinite-based approximations.
References
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Proceedings ArticleDOI

Between fully dynamic routing and robust stable routing

TL;DR: This paper proposes a strategy that can be seen as a compromise between robust routing and dynamic routing, which consists in partitioning the uncertainty set into some subsets and considering a robust routing for each subset.
Journal ArticleDOI

The Robust Network Loading Problem Under Hose Demand Uncertainty: Formulation, Polyhedral Analysis, and Computations

TL;DR: This work studies the polyhedral aspects of the NLP under hose demand uncertainty and uses the results as the basis of an efficient branch-and-cut algorithm.
Posted Content

Capacity Planning Under Uncertain Demand in Telecommunications Networks

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Domination Between Traffic Matrices

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ZIMPL User Guide

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TL;DR: A little language to translate the mathematical model of a problem into a linear or (mixed-)integer mathematical program expressed in a file format which can be read by a LP or MIP solver.
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