English

A Nearly Quadratic-Time FPTAS for Knapsack

Data Structures and Algorithms 2025-01-08 v3

Abstract

We investigate the classic Knapsack problem and propose a fully polynomial-time approximation scheme (FPTAS) that runs in O~(n+(1/ε)2)\widetilde{O}(n + (1/\varepsilon)^2) time. This improves upon the O~(n+(1/ε)11/5)\widetilde{O}(n + (1/\varepsilon)^{11/5})-time algorithm by Deng, Jin, and Mao [\textit{Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms, 2023}]. Our algorithm is the best possible (up to a polylogarithmic factor) conditioned on the conjecture that (min,+)(\min, +)-convolution has no truly subquadratic-time algorithm, since this conjecture implies that Knapsack has no O((n+1/ε)2δ)O((n + 1/\varepsilon)^{2-\delta})-time FPTAS for any constant δ>0\delta > 0.

Keywords

Cite

@article{arxiv.2308.07821,
  title  = {A Nearly Quadratic-Time FPTAS for Knapsack},
  author = {Lin Chen and Jiayi Lian and Yuchen Mao and Guochuan Zhang},
  journal= {arXiv preprint arXiv:2308.07821},
  year   = {2025}
}