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1
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Hardness Results for Total Rainbow Connection of Graphs

100%
Chen L., Huo B., Ma Y.
Discussiones Mathematicae Graph Theory
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2016
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tom 36
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nr 2
355-362
EN
A total-colored path is total rainbow if both its edges and internal vertices have distinct colors. The total rainbow connection number of a connected graph G, denoted by trc(G), is the smallest number of colors that are needed in a total-coloring of G in order to make G total rainbow connected, that is, any two vertices of G are connected by a total rainbow path. In this paper, we study the computational complexity of total rainbow connection of graphs. We show that deciding whether a given total-coloring of a graph G makes it total rainbow connected is NP-Complete. We also prove that given a graph G, deciding whether trc(G) = 3 is NP-Complete.
2
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Polynomially Bounded Sequences and Polynomial Sequences

100%
Okazaki H., Futa Y.
Formalized Mathematics
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2015
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tom 23
|
nr 3
205-213
EN
In this article, we formalize polynomially bounded sequences that plays an important role in computational complexity theory. Class P is a fundamental computational complexity class that contains all polynomial-time decision problems [11], [12]. It takes polynomially bounded amount of computation time to solve polynomial-time decision problems by the deterministic Turing machine. Moreover we formalize polynomial sequences [5].
3
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On the computational complexity of (O,P)-partition problems

80%
Kratochvíl J., Schiermeyer I.
Discussiones Mathematicae Graph Theory
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1997
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tom 17
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nr 2
253-258
EN
We prove that for any additive hereditary property P > O, it is NP-hard to decide if a given graph G allows a vertex partition V(G) = A∪B such that G[A] ∈ 𝓞 (i.e., A is independent) and G[B] ∈ P.
4
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Partial covers of graphs

80%
Fiala J., Kratochvíl J.
Discussiones Mathematicae Graph Theory
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2002
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tom 22
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nr 1
89-99
EN
Given graphs G and H, a mapping f:V(G) → V(H) is a homomorphism if (f(u),f(v)) is an edge of H for every edge (u,v) of G. In this paper, we initiate the study of computational complexity of locally injective homomorphisms called partial covers of graphs. We motivate the study of partial covers by showing a correspondence to generalized (2,1)-colorings of graphs, the notion stemming from a practical problem of assigning frequencies to transmitters without interference. We compare the problems of deciding existence of partial covers and of full covers (locally bijective homomorphisms), which were previously studied.
5
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Maximum Semi-Matching Problem in Bipartite Graphs

80%
Katrenič J., Semanišin G.
Discussiones Mathematicae Graph Theory
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2013
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tom 33
|
nr 3
559-569
EN
An (f, g)-semi-matching in a bipartite graph G = (U ∪ V,E) is a set of edges M ⊆ E such that each vertex u ∈ U is incident with at most f(u) edges of M, and each vertex v ∈ V is incident with at most g(v) edges of M. In this paper we give an algorithm that for a graph with n vertices and m edges, n ≤ m, constructs a maximum (f, g)-semi-matching in running time O(m ⋅ min [...] ) Using the reduction of [5] our result on maximum (f, g)-semi-matching problem directly implies an algorithm for the optimal semi-matching problem with running time O( [...] log n).
6
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Proof Compression and NP Versus PSPACE II: Addendum

80%
Gordeev L., Haeusler E. H.
Bulletin of the Section of Logic
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2022
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tom 51
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nr 2
197-205
EN
In our previous work we proved the conjecture NP = PSPACE by advanced proof theoretic methods that combined Hudelmaier’s cut-free sequent calculus for minimal logic (HSC) with the horizontal compressing in the corresponding minimal Prawitz-style natural deduction (ND). In this Addendum we show how to prove a weaker result NP = coNP without referring to HSC. The underlying idea (due to the second author) is to omit full minimal logic and compress only “naive” normal tree-like ND refutations of the existence of Hamiltonian cycles in given non-Hamiltonian graphs, since the Hamiltonian graph problem in NPcomplete. Thus, loosely speaking, the proof of NP = coNP can be obtained by HSC-elimination from our proof of NP = PSPACE.
7
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Minimum vertex ranking spanning tree problem for chordal and proper interval graphs

80%
Dereniowski D.
Discussiones Mathematicae Graph Theory
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2009
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tom 29
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nr 2
253-261
EN
A vertex k-ranking of a simple graph is a coloring of its vertices with k colors in such a way that each path connecting two vertices of the same color contains a vertex with a bigger color. Consider the minimum vertex ranking spanning tree (MVRST) problem where the goal is to find a spanning tree of a given graph G which has a vertex ranking using the minimal number of colors over vertex rankings of all spanning trees of G. K. Miyata et al. proved in [NP-hardness proof and an approximation algorithm for the minimum vertex ranking spanning tree problem, Discrete Appl. Math. 154 (2006) 2402-2410] that the decision problem: given a simple graph G, decide whether there exists a spanning tree T of G such that T has a vertex 4-ranking, is NP-complete. In this paper we improve this result by proving NP-hardness of finding for a given chordal graph its spanning tree having vertex 3-ranking. This bound is the best possible. On the other hand we prove that MVRST problem can be solved in linear time for proper interval graphs.
8
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Proof Compression and NP Versus PSPACE II

80%
Gordeev L., Haeusler E. H.
Bulletin of the Section of Logic
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2020
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tom 49
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nr 3
213-230
EN
We upgrade [3] to a complete proof of the conjecture NP = PSPACE that is known as one of the fundamental open problems in the mathematical theory of computational complexity; this proof is based on [2]. Since minimal propositional logic is known to be PSPACE complete, while PSPACE to include NP, it suffices to show that every valid purely implicational formula ρ has a proof whose weight (= total number of symbols) and time complexity of the provability involved are both polynomial in the weight of ρ. As is [3], we use proof theoretic approach. Recall that in [3] we considered any valid ρ in question that had (by the definition of validity) a “short” tree-like proof π in the Hudelmaier-style cutfree sequent calculus for minimal logic. The “shortness” means that the height of π and the total weight of different formulas occurring in it are both polynomial in the weight of ρ. However, the size (= total number of nodes), and hence also the weight, of π could be exponential in that of ρ. To overcome this trouble we embedded π into Prawitz’s proof system of natural deductions containing single formulas, instead of sequents. As in π, the height and the total weight of different formulas of the resulting tree-like natural deduction ∂1 were polynomial, although the size of ∂1 still could be exponential, in the weight of ρ. In our next, crucial move, ∂1 was deterministically compressed into a “small”, although multipremise, dag-like deduction ∂ whose horizontal levels contained only mutually different formulas, which made the whole weight polynomial in that of ρ. However, ∂ required a more complicated verification of the underlying provability of ρ. In this paper we present a nondeterministic compression of ∂ into a desired standard dag-like deduction ∂0 that deterministically proves ρ in time and space polynomial in the weight of ρ.2 Together with [3] this completes the proof of NP = PSPACE.Natural deductions are essential for our proof. Tree-to-dag horizontal compression of π merging equal sequents, instead of formulas, is (possible but) not sufficient, since the total number of different sequents in π might be exponential in the weight of ρ – even assuming that all formulas occurring in sequents are subformulas of ρ. On the other hand, we need Hudelmaier’s cutfree sequent calculus in order to control both the height and total weight of different formulas of the initial tree-like proof π, since standard Prawitz’s normalization although providing natural deductions with the subformula property does not preserve polynomial heights. It is not clear yet if we can omit references to π even in the proof of the weaker result NP = coNP.
9
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The NP-completeness of automorphic colorings

80%
Mazzuoccolo G.
Discussiones Mathematicae Graph Theory
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2010
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tom 30
|
nr 4
705-710
EN
Given a graph G, an automorphic edge(vertex)-coloring of G is a proper edge(vertex)-coloring such that each automorphism of the graph preserves the coloring. The automorphic chromatic index (number) is the least integer k for which G admits an automorphic edge(vertex)-coloring with k colors. We show that it is NP-complete to determine the automorphic chromatic index and the automorphic chromatic number of an arbitrary graph.
10
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Internet shopping optimization problem

70%
Błażewicz J., Kovalyov M., Musiał J., Urbański A., Wojciechowski A.
International Journal of Applied Mathematics and Computer Science
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2010
|
tom 20
|
nr 2
385-390
EN
A high number of Internet shops makes it difficult for a customer to review manually all the available offers and select optimal outlets for shopping. A partial solution to the problem is brought by price comparators which produce price rankings from collected offers. However, their possibilities are limited to a comparison of offers for a single product requested by the customer. The issue we investigate in this paper is a multiple-item multiple-shop optimization problem, in which total expenses of a customer to buy a given set of items should be minimized over all available offers. In this paper, the Internet Shopping Optimization Problem (ISOP) is defined in a formal way and a proof of its strong NP-hardness is provided. We also describe polynomial time algorithms for special cases of the problem.
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