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https://doi.org/10.3...arrow_drop_down
https://doi.org/10.3233/faia20...
Part of book or chapter of book . 2020 . Peer-reviewed
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Part of book or chapter of book . 2020
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Object Allocation and Positive Graph Externalities

Authors: Dimitris Fotakis 0001; Laurent Gourvès; Stelios Kasouridis; Aris Pagourtzis;

Object Allocation and Positive Graph Externalities

Abstract

The worth of an entity does not only come from its intrinsic value. The other entities in the neighborhood also influence this quantity. We introduce and study a model where some heterogeneous objects have to be placed on a network so that the elements with high value may exert a positive externality on neighboring elements whose value is lower. We aim at maximizing this positive influence called graph externality. By exploiting a connection with the minimum dominating set problem, we prove that the problem is NP-hard when the maximum degree is 3, but polynomial time solvable when the maximum degree is 2. We also present exact and approximation algorithms for special cases. In particular, if only two valuations exist, then a natural greedy strategy, which works well for maximum coverage problems, leads to a constant approximation algorithm. With extensive numerical experiments we finally show that a greedy algorithm performs very well for general valuations.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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