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Erschienen in: Journal of Combinatorial Optimization 3/2022

06.01.2020

Robustly assigning unstable items

verfasst von: Ananya Christman, Christine Chung, Nicholas Jaczko, Scott Westvold, David S. Yuen

Erschienen in: Journal of Combinatorial Optimization | Ausgabe 3/2022

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Abstract

We study the robust assignment problem where the goal is to assign items of various types to containers without exceeding container capacity. We seek an assignment that uses the fewest number of containers and is robust, that is, if any item of type \(t_i\) becomes corrupt causing the containers with type \(t_i\) to become unstable, every other item type \(t_j \ne t_i\) is still assigned to a stable container. We begin by presenting an optimal polynomial-time algorithm that finds a robust assignment using the minimum number of containers for the case when the containers have infinite capacity. Then we consider the case where all containers have some fixed capacity and give an optimal polynomial-time algorithm for the special case where each type of item has the same size. When the sizes of the item types are nonuniform, we provide a polynomial-time 2-approximation for the problem. We also prove that the approximation ratio of our algorithm is no lower than 1.813. We conclude with an experimental evaluation of our algorithm.

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Fußnoten
1
Note that \(S_i \subseteq S_j\) is the condition for the general case; for the case where \(k_i=k_j\) for all \(i,j \in \{1,2,\ldots ,n\}\), the condition is \(S_i=S_j\).
 
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Metadaten
Titel
Robustly assigning unstable items
verfasst von
Ananya Christman
Christine Chung
Nicholas Jaczko
Scott Westvold
David S. Yuen
Publikationsdatum
06.01.2020
Verlag
Springer US
Erschienen in
Journal of Combinatorial Optimization / Ausgabe 3/2022
Print ISSN: 1382-6905
Elektronische ISSN: 1573-2886
DOI
https://doi.org/10.1007/s10878-019-00515-w

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