
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.
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
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
| 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). | 1 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
