A linear time algorithm for the robust recoverable selection problem

Thomas Lachmann; Stefan Lendl; Gerhard J. Woeginger

doi:10.1016/j.dam.2020.08.012

A linear time algorithm for the robust recoverable selection problem

Thomas Lachmann, Stefan Lendl^*, Gerhard J. Woeginger

^*Corresponding author for this work

Institute of Discrete Mathematics (5050)

Research output: Contribution to journal › Article › peer-review

Abstract

The feasible solutions in the robust recoverable selection problem are subsets of size p that are to be selected from a ground set of size n. The objective is to construct a feasible solution in two sequential stages with two separate (but interleaved) cost structures. The fastest algorithm for this problem in the literature up to now has quadratic running time. We improve on this by developing an algorithm with linear running time.

Original language	English
Pages (from-to)	94-107
Number of pages	14
Journal	Discrete Applied Mathematics
Volume	303
Early online date	Sept 2020
DOIs	https://doi.org/10.1016/j.dam.2020.08.012
Publication status	Published - 15 Nov 2021

Keywords

Computational complexity
Robust optimization
Selection problem

ASJC Scopus subject areas

Applied Mathematics
Discrete Mathematics and Combinatorics

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10.1016/j.dam.2020.08.012Licence: CC BY-NC-ND 4.0

Cite this

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KW - Robust optimization

KW - Selection problem

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A linear time algorithm for the robust recoverable selection problem

Abstract

Keywords

ASJC Scopus subject areas

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