Incremental Maximization via Continuization
Abstract
We consider the problem of finding an incremental solution to a cardinality-constrained maximization problem that not only captures the solution for a fixed cardinality, but also describes how to gradually grow the solution as the cardinality bound increases. The goal is to find an incremental solution that guarantees a good competitive ratio against the optimum solution for all cardinalities simultaneously. The central challenge is to characterize maximization problems where this is possible, and to determine the best-possible competitive ratio that can be attained. A lower bound of and an upper bound of are known on the competitive ratio for monotone and accountable objectives [Bernstein et al., Math. Prog., 2022], which capture a wide range of maximization problems. We introduce a continuization technique and identify an optimal incremental algorithm that provides strong evidence that is the best-possible competitive ratio. Using this continuization, we obtain an improved lower bound of by studying a particular recurrence relation whose characteristic polynomial has complex roots exactly beyond the lower bound. Based on the optimal continuous algorithm combined with a scaling approach, we also provide a -competitive randomized algorithm. We complement this by a randomized lower bound of via Yao's principle.
Cite
@article{arxiv.2305.01310,
title = {Incremental Maximization via Continuization},
author = {Yann Disser and Max Klimm and Kevin Schewior and David Weckbecker},
journal= {arXiv preprint arXiv:2305.01310},
year = {2023}
}