Computing the Polytope Diameter is Even Harder than NP-hard (Already for Perfect Matchings)
Lasse Wulf

TL;DR
This paper proves that computing the diameter of bipartite perfect matching polytopes is $\Pi^p_2$-hard, answering a 30-year-old question, and establishes inapproximability results for the circuit diameter of these polytopes.
Contribution
It establishes the $\Pi^p_2$-completeness of computing the bipartite perfect matching polytope diameter and proves inapproximability bounds, advancing understanding of polytope diameter complexity.
Findings
Computing the bipartite perfect matching polytope diameter is $\Pi^p_2$-hard.
The problem is in $\Pi^p_2$, confirming $\Pi^p_2$-completeness.
The circuit diameter cannot be approximated within a factor better than $(1 + \varepsilon)$.
Abstract
The diameter of a polytope is a fundamental geometric parameter that plays a crucial role in understanding the efficiency of the simplex method. Despite its central nature, the computational complexity of computing the diameter of a given polytope is poorly understood. Already in 1994, Frieze and Teng [Comp. Compl.] recognized the possibility that this task could potentially be harder than NP-hard, and asked whether the corresponding decision problem is complete for the second stage of the polynomial hierarchy, i.e. -complete. In the following years, partial results could be obtained. In a cornerstone result, Frieze and Teng themselves proved weak NP-hardness for a family of custom defined polytopes. Sanit\`a [FOCS18] in a break-through result proved that already for the much simpler fractional matching polytope the problem is strongly NP-hard. Very recently, Steiner and…
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Taxonomy
TopicsAlgorithms and Data Compression · semigroups and automata theory · graph theory and CDMA systems
