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New research examines MAXSTP computational complexity

A new research paper published on arXiv explores the computational complexity of the Maximum Satisfiability of Simple Temporal Problems (MAXSTP). The study analyzes MAXSTP's parameterized complexity concerning instance scale, coefficient magnitude, and structural graph parameters like treewidth and vertex cover. The findings indicate that MAXSTP is generally harder to solve than optimizing qualitative CSPs, with fixed-parameter tractability achievable for certain parameter combinations. AI

RANK_REASON The cluster contains a single academic paper published on arXiv detailing computational complexity research. [lever_c_demoted from research: ic=1 ai=0.4]

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New research examines MAXSTP computational complexity

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Johannes K. Fichte, Johanna Groven, Peter Jonsson, Victor Lagerkvist, Jorke M. de Vlas ·

    Maximum Satisfiability of Simple Temporal Problems

    arXiv:2607.23785v1 Announce Type: cross Abstract: The Simple Temporal Problem (STP) is a core framework for quantitative temporal constraints. As STP data can be inconsistent, we study MAXSTP: compute a maximum-cardinality consistent subset of constraints. This extension is NP-ha…