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Packing Under Convex Quadratic Constraints

Packing under convex quadratic constraints
Authors: Max Klimm; Marc E. Pfetsch; Rico Raber; Martin Skutella;

Packing Under Convex Quadratic Constraints

Abstract

AbstractWe consider a general class of binary packing problems with a convex quadratic knapsack constraint. We prove that these problems are$$\mathsf {APX}$$APX-hard to approximate and present constant-factor approximation algorithms based upon two different algorithmic techniques: a rounding technique tailored to a convex relaxation in conjunction with a non-convex relaxation, and a greedy strategy. We further show that a combination of these techniques can be used to yield a monotone algorithm leading to a strategyproof mechanism for a game-theoretic variant of the problem. Finally, we present a computational study of the empirical approximation of these algorithms for problem instances arising in the context of real-world gas transport networks.

Country
Germany
Keywords

Combinatorial optimization, Analysis of algorithms and problem complexity, 500 Naturwissenschaften und Mathematik::510 Mathematik::510 Mathematik, greedy strategy, convex quadratic constraints, Programming involving graphs or networks, binary packing problem, constant-factor approximation, constant-factor approximation algorithms, Optimization and Control (math.OC), FOS: Mathematics, Mathematics - Optimization and Control

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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
Green
hybrid