2026-08-06T10:35:49Z https://drops.dagstuhl.de/oai

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A Structural Investigation of the Approximability of Polynomial-Time Problems Bringmann, Karl Cassis, Alejandro Fischer, Nick Künnemann, Marvin Classification Theorems Hardness of Approximation in P Fine-grained Complexity Theory An extensive research effort targets optimal (in)approximability results for various NP-hard optimization problems. Notably, the works of (Creignou'95) as well as (Khanna, Sudan, Trevisan, Williamson'00) establish a tight characterization of a large subclass of MaxSNP, namely Boolean MaxCSPs and further variants, in terms of their polynomial-time approximability. Can we obtain similarly encompassing characterizations for classes of polynomial-time optimization problems? To this end, we initiate the systematic study of a recently introduced polynomial-time analogue of MaxSNP, which includes a large number of well-studied problems (including Nearest and Furthest Neighbor in the Hamming metric, Maximum Inner Product, optimization variants of k-XOR and Maximum k-Cover). Specifically, for each k, MaxSP_k denotes the class of O(m^k)-time problems of the form max_{x_1,… , x_k} #{y : ϕ(x_1,… ,x_k,y)} where ϕ is a quantifier-free first-order property and m denotes the size of the relational structure. Assuming central hypotheses about clique detection in hypergraphs and exact Max-3-SAT}, we show that for any MaxSP_k problem definable by a quantifier-free m-edge graph formula φ, the best possible approximation guarantee in faster-than-exhaustive-search time O(m^{k-δ})falls into one of four categories: - optimizable to exactness in time O(m^{k-δ}), - an (inefficient) approximation scheme, i.e., a (1+ε)-approximation in time O(m^{k-f(ε)}), - a (fixed) constant-factor approximation in time O(m^{k-δ}), or - a nm^ε-approximation in time O(m^{k-f(ε)}). We obtain an almost complete characterization of these regimes, for MaxSP_k as well as for an analogously defined minimization class MinSP_k. As our main technical contribution, we show how to rule out the existence of approximation schemes for a large class of problems admitting constant-factor approximations, under a hypothesis for exact Sparse Max-3-SAT algorithms posed by (Alman, Vassilevska Williams'20). As general trends for the problems we consider, we observe: (1) Exact optimizability has a simple algebraic characterization, (2) only few maximization problems do not admit a constant-factor approximation; these do not even have a subpolynomial-factor approximation, and (3) constant-factor approximation of minimization problems is equivalent to deciding whether the optimum is equal to 0. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Karl Bringmann and Alejandro Cassis and Nick Fischer and Marvin Künnemann 2022 Is Part Of LIPIcs, Volume 229, 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ICALP.2022.30 urn:nbn:de:0030-drops-163713 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2022.30 eng https://creativecommons.org/licenses/by/4.0/legalcode