Generalized paths and cycles in semicomplete multipartite digraphs

A directed graph D is semicomplete if for every pair x, y of vertices of D, there is at least one arc between x and y. Thus, a tournament is a semicomplete digraph. In the Directed Component Order Connectivity (DCOC) problem, given a digraph D=(V,A) and a pair of natural numbers k and ell , we are to decide whether there is a subset X of V of size k such that the largest strongly connected component in D-X has at most ell vertices. Note that DCOC reduces to the Directed Feedback Vertex Set problem for ell =1. We study the parameterized complexity of DCOC for general and semicomplete digraphs with the following parameters: k, ell ,ell +k and n-ell . In particular, we prove that DCOC with parameter k on semicomplete digraphs can be solved in time O^*(2^{16k}) but not in time O^*(2^{o(k)}) unless the Exponential Time Hypothesis (ETH) fails. The upper bound O^*(2^{16k}) implies the upper bound O^*(2^{16(n-ell )}) for the parameter n-ell . We complement the latter by showing that there is no algorithm of time complexity O^*(2^{o({n-ell })}) unless ETH fails. Finally, we improve (in dependency on ell ) the upper bound of Göke, Marx and Mnich (2019) for the time complexity of DCOC with parameter ell +k on general digraphs from O^*(2^{O(kell log (kell ))}) to O^*(2^{O(klog (kell ))}). Note that Drange, Dregi and van ’t Hof (2016) proved that even for the undirected version of DCOC on split graphs there is no algorithm of running time O^*(2^{o(klog ell )}) unless ETH fails and it is a long-standing problem to decide whether Directed Feedback Vertex Set admits an algorithm of time complexity O^*(2^{o(klog k)}).

Decomposing locally semicomplete digraphs into strong spanning subdigraphs

A polynomial algorithm for hamiltonian-connectedness in semicomplete digraphs

The so-called Kelly conjecture1 A proof of the Kelly conjecture for large k has been announced by R. Haggkvist at several conferences and in [5] but to this date no proof has been published.states that every regular tournament on 2k+1 vertices has a decomposition into k-arc-disjoint hamiltonian cycles. In this paper we formulate a generalization of that conjecture, namely we conjecture that every k-arc-strong tournament contains k arc-disjoint spanning strong subdigraphs. We prove several results which support the conjecture:If D = (V, A) is a 2-arc-strong semicomplete digraph then it contains 2 arc-disjoint spanning strong subdigraphs except for one digraph on 4 vertices.Every tournament which has a non-trivial cut (both sides containing at least 2 vertices) with precisely k arcs in one direction contains k arc-disjoint spanning strong subdigraphs. In fact this result holds even for semicomplete digraphs with one exception on 4 vertices.Every k-arc-strong tournament with minimum in- and out-degree at least 37k contains k arc-disjoint spanning subdigraphs H1, H2, . . . , Hk such that each Hi is strongly connected.The last result implies that if T is a 74k-arc-strong tournament with speci.ed not necessarily distinct vertices u1, u2, . . . , uk, v1, v2, . . . , vk then T contains 2k arc-disjoint branchings $$F^{ - }_{{u_{1} }} ,F^{ - }_{{u_{2} }} ,...,F^{ - }_{{u_{k} }} ,F^{ + }_{{v_{1} }} ,F^{ + }_{{v_{2} }} ,...,F^{ + }_{{v_{k} }}$$ where $$F^{ - }_{{u_{i} }}$$ is an in-branching rooted at the vertex ui and $$F^{ + }_{{v_{i} }}$$ is an out-branching rooted at the vertex vi, i=1,2, . . . , k. This solves a conjecture of Bang-Jensen and Gutin [3].We also discuss related problems and conjectures.

Minimum cost and list homomorphisms to semicomplete digraphs

The so‐called weak‐2‐linkage problem asks for a given digraph and distinct vertices of whether has arc‐disjoint paths so that is an ‐path for . This problem is NP‐complete for general digraphs but the first author showed that the problem is polynomially solvable and that all exceptions can be characterized when is a semicomplete digraph, that is, a digraph with no pair of nonadjacent vertices. In this paper we extend these results to paths which are both edge‐disjoint and arc‐disjoint in semicomplete mixed graphs, that is, a mixed graph in which every pair of distinct vertices has either an arc, an edge, or both an arc and an edge between them. We give a complete characterization of the negative instances and explain how this gives rise to a polynomial algorithm for the problem.

Molecular computing has proved its possibility to solve weighted graph problem such as Hamiltonian Path Problem (HPP), Traveling Salesman Problem (TSP) and the Shortest Path Problem (SPP). Normally, in molecular computation, the DNA sequences used for the computation should be critically designed in order to reduce error that could occur during computation. In the previous paper, we have proposed a readout method tailored specifically to HPP in DNA Computing using real-time PCR for output visualization. Six nodes of HPP was considered. Based on the example instance, the method requires 11 oligonucleotides, where 6 oligonucleotides are for the nodes and 5 oligonucleotides are for the edges. Three TaqMan probes and five primers are required as well. In this study, a procedure for DNA sequence design is presented in order to obtain good sequences for those nodes, primers, and probes. The experiment is done based on the generated DNA sequences and the Hamiltonian Path can be determined successfully.

Not being (super)thin or solid is hard: A study of grid Hamiltonicity

The Hamiltonian cycle problem is a well-known NP-complete problem in graph theory. This problem relates to lots of practical problems such as designing very large scale integration (VLSI) and travel-ling salesman problem (TSP). Since it is NP-complete, there is no efficient algorithm to solve the Hamiltonian cycle problem, and hence, its solution is valuable. In this paper, we propose new physical zero-knowledge proof protocols for the Hamiltonian cycle problem, whereby an entity can prove its knowledge of a solution to another entity without leaking any information about the valuable solution. Our protocols are more efficient than the previous protocols. We also propose a physical zero-knowledge proof protocol for TSP, one of whose building blocks is a new representation of an integer commitment with a secure addition protocol.

Kombinatorische entscheidungsprobleme: Methoden und anwendungen; fortbildungskurs des instituts für operations research der ETH Zürich: Thomas M. Liebling, Max Rössler (Eds.) Springer, Berlin, 1978, 206 pages, Dfl. 32.75 Soft cover

Hamiltonian problems in directed graphs with simple row patterns

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Stochastic processes, estimation, and control: The entropy approach: By George N. Saridis

We consider the Hamiltonian cycle problem on a given graph $G$. With such a graph we can associate a family $\mathcal{F}$ of probability transition matrices of Markov chains whose entries represent the probabilities of traversing corresponding arcs of the graph. When the underlying graph is Hamiltonian, we show the transition probability matrix induced by a Hamiltonian cycle maximizes—over $\mathcal{F}$—the determinant of a matrix that is a rank-one correction of the generator matrix of a Markov chain. In the case when the graph does not possess a Hamiltonian cycle, the above maximization yields a transition matrix of a chain with a longest simple cycle (in $G$) comprising that chain's unique ergodic class. These problems also have analogous eigenvalue interpretations.

Given a graph with colored edges, a Hamiltonian cycle is called alternating if its successive edges differ in color. The problem of finding such a cycle, even for 2-edge-colored graphs, is trivially NP-complete, while it is known to be polynomial for 2-edge-colored complete graphs. In this paper we study the parallel complexity of finding such a cycle, if any, in 2-edge-colored complete graphs. We give a new characterization for such a graph admitting an alternating Hamiltonian cycle which allows us to derive a parallel algorithm for the problem. We prove that the alternating Hamiltonian cycle problem is in RNC and it belongs to NC if the perfect matching problem does. In addition, our parallel algorithm improves the complexity of the best known sequential algorithm by a factor of O(√n).