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Hard Problem Generation for MKP

Authors: Maria A. Osorio; German Cuaya-Simbro;

Hard Problem Generation for MKP

Abstract

We developed generators that produce challenging MKP instances. Our approaches uses independently exponential distributions over a wide range to generate the constraint coefficients, and the corresponding average for each variable is used to calculate directly correlated coefficients in the objective function. RHS values are a percentage of the sum of constraint coefficients. We present a comparative table with the average performance for the most important generators reported in the literature and our generators, over a wide range of parameters and instances in the OR library.

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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!
1
Average
Average
Average
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