The minimum vulnerability problem on specific graph classes

Suppose that each edge e of an undirected graph G is associated with three nonnegative integers \(\mathsf{cost}(e)\), \(\mathsf{vul}(e)\) and \(\mathsf{cap}(e)\), called the cost, vulnerability and capacity of e, respectively. Then, we consider the problem of finding \(k\) paths in G between two prescribed vertices with the minimum total cost; each edge e can be shared without any cost by at most \(\mathsf{vul}(e)\) paths, and can be shared by more than \(\mathsf{vul}(e)\) paths if we pay \(\mathsf{cost}(e)\), but cannot be shared by more than \(\mathsf{cap}(e)\) paths even if we pay the cost for e. This problem generalizes the disjoint path problem, the minimum shared edges problem and the minimum edge cost flow problem for undirected graphs, and it is known to be NP-hard. In this paper, we study the problem from the viewpoint of specific graph classes, and give three results. We first show that the problem is NP-hard even for bipartite outerplanar graphs, 2-trees, graphs with pathwidth two, complete bipartite graphs, and complete graphs. We then give a pseudo-polynomial-time algorithm for bounded treewidth graphs. Finally, we give a fixed-parameter algorithm for chordal graphs when parameterized by the number \(k\) of required paths.     

Roman game domination number of a graph

The Roman game domination number of an undirected graph G is defined by the following game. Players \(\mathcal {A}\) and \(\mathcal {D}\) orient the edges of the graph G alternately, with \(\mathcal {D}\) playing first, until all edges are oriented. Player \(\mathcal {D}\) (frequently called Dominator) tries to minimize the Roman domination number of the resulting digraph, while player \(\mathcal {A}\) (Avoider) tries to maximize it. This game gives a unique number depending only on G, if we suppose that both \(\mathcal {A}\) and \(\mathcal {D}\) play according to their optimal strategies. This number is called the Roman game domination number of G and is denoted by \(\gamma _{Rg}(G)\). In this paper we initiate the study of the Roman game domination number of a graph and we establish some bounds on \(\gamma _{Rg}(G)\). We also determine the Roman game domination number for some classes of graphs.     

Matching colored points with rectangles

Let S be a point set in the plane such that each of its elements is colored either red or blue. A matching of S with rectangles is any set of pairwise-disjoint axis-aligned closed rectangles such that each rectangle contains exactly two points of S. Such a matching is monochromatic if every rectangle contains points of the same color, and is bichromatic if every rectangle contains points of different colors. We study the following two problems: (1) Find a maximum monochromatic matching of S with rectangles. (2) Find a maximum bichromatic matching of S with rectangles. For each problem we provide a polynomial-time approximation algorithm that constructs a matching with at least 1 / 4 of the number of rectangles of an optimal matching. We show that the first problem is \(\mathsf {NP}\)-hard even if either the matching rectangles are restricted to axis-aligned segments or S is in general position, that is, no two points of S share the same x or y coordinate. We further show that the second problem is also \(\mathsf {NP}\)-hard, even if S is in general position. These \(\mathsf {NP}\)-hardness results follow by showing that deciding the existence of a matching that covers all points is \(\mathsf {NP}\)-complete in each case. Additionally, we prove that it is \(\mathsf {NP}\)-complete to decide the existence of a matching with rectangles that cover all points in the case where all the points have the same color, solving an open problem of Bereg et al. (Comput Geom 42(2):93–108, 2009).     

On minimally 2-connected graphs with generalized connectivity $$\kappa _{3}=2$$

For \(S\subseteq G\), let \(\kappa (S)\) denote the maximum number r of edge-disjoint trees \(T_1, T_2, \ldots , T_r\) in G such that \(V(T_i)\cap V(T_j)=S\) for any \(i,j\in \{1,2,\ldots ,r\}\) and \(i\ne j\). For every \(2\le k\le n\), the k-connectivity of G, denoted by \(\kappa _k(G)\), is defined as \(\kappa _k(G)=\hbox {min}\{\kappa (S)| S\subseteq V(G)\ and\ |S|=k\}\). Clearly, \(\kappa _2(G)\) corresponds to the traditional connectivity of G. In this paper, we focus on the structure of minimally 2-connected graphs with \(\kappa _{3}=2\). Denote by \(\mathcal {H}\) the set of minimally 2-connected graphs with \(\kappa _{3}=2\). Let \(\mathcal {B}\subseteq \mathcal {H}\) and every graph in \(\mathcal {B}\) is either \(K_{2,3}\) or the graph obtained by subdividing each edge of a triangle-free 3-connected graph. We obtain that \(H\in \mathcal {H}\) if and only if \(H\in \mathcal {B}\) or H can be constructed from one or some graphs \(H_{1},\ldots ,H_{k}\) in \(\mathcal {B}\) (\(k\ge 1\)) by applying some operations recursively.     

Approximation algorithms for minimum weight partial connected set cover problem

In the Minimum Weight Partial Connected Set Cover problem, we are given a finite ground set \(U\), an integer \(q\le |U|\), a collection \(\mathcal {E}\) of subsets of \(U\), and a connected graph \(G_{\mathcal {E}}\) on vertex set \(\mathcal {E}\), the goal is to find a minimum weight subcollection of \(\mathcal {E}\) which covers at least \(q\) elements of \(U\) and induces a connected subgraph in \(G_{\mathcal {E}}\). In this paper, we derive a “partial cover property” for the greedy solution of the Minimum Weight Set Cover problem, based on which we present (a) for the weighted version under the assumption that any pair of sets in \(\mathcal {E}\) with nonempty intersection are adjacent in \(G_{\mathcal {E}}\) (the Minimum Weight Partial Connected Vertex Cover problem falls into this range), an approximation algorithm with performance ratio \(\rho (1+H(\gamma ))+o(1)\), and (b) for the cardinality version under the assumption that any pair of sets in \(\mathcal {E}\) with nonempty intersection are at most \(d\)-hops away from each other (the Minimum Partial Connected \(k\)-Hop Dominating Set problem falls into this range), an approximation algorithm with performance ratio \(2(1+dH(\gamma ))+o(1)\), where \(\gamma =\max \{|X|:X\in \mathcal {E}\}\), \(H(\cdot )\) is the Harmonic number, and \(\rho \) is the performance ratio for the Minimum Quota Node-Weighted Steiner Tree problem.     

Further results on the reciprocal degree distance of graphs

The reciprocal degree distance of a simple connected graph \(G=(V_G, E_G)\) is defined as \(\bar{R}(G)=\sum _{u,v \in V_G}(\delta _G(u)+\delta _G(v))\frac{1}{d_G(u,v)}\), where \(\delta _G(u)\) is the vertex degree of \(u\), and \(d_G(u,v)\) is the distance between \(u\) and \(v\) in \(G\). The reciprocal degree distance is an additive weight version of the Harary index, which is defined as \(H(G)=\sum _{u,v \in V_G}\frac{1}{d_G(u,v)}\). In this paper, the extremal \(\bar{R}\)-values on several types of important graphs are considered. The graph with the maximum \(\bar{R}\)-value among all the simple connected graphs of diameter \(d\) is determined. Among the connected bipartite graphs of order \(n\), the graph with a given matching number (resp. vertex connectivity) having the maximum \(\bar{R}\)-value is characterized. Finally, sharp upper bounds on \(\bar{R}\)-value among all simple connected outerplanar (resp. planar) graphs are determined.     

Nordhaus–Gaddum bounds for total Roman domination

A Nordhaus–Gaddum-type result is a lower or an upper bound on the sum or the product of a parameter of a graph and its complement. In this paper we continue the study of Nordhaus–Gaddum bounds for the total Roman domination number \(\gamma _{tR}\). Let G be a graph on n vertices and let \(\overline{G}\) denote the complement of G, and let \(\delta ^*(G)\) denote the minimum degree among all vertices in G and \(\overline{G}\). For \(\delta ^*(G)\ge 1\), we show that (i) if G and \(\overline{G}\) are connected, then \((\gamma _{tR}(G)-4)(\gamma _{tR}(\overline{G})-4)\le 4\delta ^*(G)-4\), (ii) if \(\gamma _{tR}(G), \gamma _{tR}(\overline{G})\ge 8\), then \(\gamma _{tR}(G)+\gamma _{tR}(\overline{G})\le 2\delta ^*(G)+5\) and (iii) \(\gamma _{tR}(G)+\gamma _{tR}(\overline{G})\le n+5\) and \(\gamma _{tR}(G)\gamma _{tR}(\overline{G})\le 6n-5\).     

Bounded information dissemination in multi-channel wireless networks

More and more wireless networks and devices now operate on multiple channels, which poses the question: How to use multiple channels to speed up communication? In this paper, we answer this question for the case of wireless ad-hoc networks where information dissemination is a primitive operation. Specifically, we propose a randomized distributed algorithm for information dissemination that is very near the optimal. The general information dissemination problem is to deliver \(k\) information packets, stored initially in \(k\) different nodes (the packet holders), to all the nodes in the network, and the objective is to minimize the time needed. With an eye toward the reality, we assume a model where the packet holders are determined by an adversary, and neither the number \(k\) nor the identities of packet holders are known to the nodes in advance. Not knowing the value of \(k\) sets this problem apart from broadcasting and all-to-all communication (gossiping). We study the information dissemination problem in single-hop networks with bounded-size messages. We present a randomized algorithm which can disseminate all packets in \(O(k(\frac{1}{\mathcal {F}}+\frac{1}{\mathcal {P}})+\log ^2n)\) rounds with high probability, where \(\mathcal {F}\) is the number of available channels and \(\mathcal {P}\) is the bound on the number of packets a message can carry. Compared with the lower bound \(\varOmega (k(\frac{1}{\mathcal {F}}+\frac{1}{\mathcal {P}}))\), the given algorithm is very close to the asymptotical optimal except for an additive factor. Our result provides the first solid evidence that multiple channels can indeed substantially speed up information dissemination, which also breaks the \(\varOmega (k)\) lower bound that holds for single-channel networks (even if \(\mathcal {P}\) is infinity).     

On approximating optimal weight “no”-certificates in weighted difference constraint systems

This paper is concerned with the design and analysis of approximation algorithms for the problem of determining the least weight refutation in a weighted difference constraint system. Recall that a difference constraint is a linear constraint of the form \(x_{i}-x_{j} \le b_{ij}\) and a conjunction of such constraints is called a difference constraint system (DCS). In a weighted DCS (WDCS), a positive weight is associated with each constraint. Every infeasible constraint system has a refutation, which attests to its infeasibility. In the case of a DCS, this refutation is a subset of the input constraints, which when added together produces a contradiction of the form \(0 \le -b\), \(b> 0\). It follows that every refutation acts as a “no”-certificate. The length of a refutation is the number of constraints used in the derivation of a contradiction. Associated with a DCS \(\mathbf{D: A\cdot x \le b}\) is its constraint network \(\mathbf{G= \langle V,E, b \rangle }\). It is well-known that \(\mathbf{D}\) is infeasible if and only if \(\mathbf{G}\) contains a simple, negative cost cycle. Previous research has established that every negative cost cycle of length k in \(\mathbf{G}\) corresponds exactly to a refutation of \(\mathbf{D}\) using k constraints. It follows that the shortest refutation of \(\mathbf{D}\) (i.e., the refutation which uses the fewest number of constraints) corresponds to the length of the shortest negative cycle in \(\mathbf{G}\). The constraint network of a WDCS is represented by a constraint network \(\mathbf{G = \langle V, E, b, l \rangle }\), where \(\mathbf{l}:\mathbf{E \rightarrow \mathbb {N}}\) represents a function which associates a positive, integral length with each edge in \(\mathbf{G}\). In the case of a WDCS, the weight of a refutation is defined as the sum of the lengths of the edges corresponding to the refutation. The problem of finding the minimum weight refutation in a WDCS is called the weighted optimal length resolution refutation (WOLRR) problem and is known to be NP-hard. In this paper, we describe a pseudo-polynomial time algorithm for the WOLRR problem and convert it into a fully polynomial time approximation scheme (FPTAS).     

Almost separable matrices

An \(m\times n\) matrix \(\mathsf {A}\) with column supports \(\{S_i\}\) is k-separable if the disjunctions \(\bigcup _{i \in \mathcal {K}} S_i\) are all distinct over all sets \(\mathcal {K}\) of cardinality k. While a simple counting bound shows that \(m > k \log _2 n/k\) rows are required for a separable matrix to exist, in fact it is necessary for m to be about a factor of k more than this. In this paper, we consider a weaker definition of ‘almost k-separability’, which requires that the disjunctions are ‘mostly distinct’. We show using a random construction that these matrices exist with \(m = O(k \log n)\) rows, which is optimal for \(k = O(n^{1-\beta })\). Further, by calculating explicit constants, we show how almost separable matrices give new bounds on the rate of nonadaptive group testing.     

Complexity of domination,hamiltonicity and treewidth for tree convex bipartite graphs

In this paper, we first give the definition of randomized time-varying knapsack problems (\(\textit{RTVKP}\)) and its mathematic model, and analyze the character about the various forms of \(\textit{RTVKP}\). Next, we propose three algorithms for \(\textit{RTVKP}\): (1) an exact algorithm with pseudo-polynomial time based on dynamic programming; (2) a 2-approximation algorithm for \(\textit{RTVKP}\) based on greedy algorithm; (3) a heuristic algorithm by using elitists model based on genetic algorithms. Finally, we advance an evaluation criterion for the algorithm which is used for solving dynamic combinational optimization problems, and analyze the virtue and shortage of three algorithms above by using the criterion. For the given three instances of \(\textit{RTVKP}\), the simulation computation results coincide with the theory analysis.     

On the odd girth and the circular chromatic number of generalized Petersen graphs

A class \(\mathcal{G}\) of simple graphs is said to be girth-closed (odd-girth-closed) if for any positive integer g there exists a graph \(\mathrm {G} \in \mathcal{G}\) such that the girth (odd-girth) of \(\mathrm {G}\) is \(\ge g\). A girth-closed (odd-girth-closed) class \(\mathcal{G}\) of graphs is said to be pentagonal (odd-pentagonal) if there exists a positive integer \(g^*\) depending on \(\mathcal{G}\) such that any graph \(\mathrm {G} \in \mathcal{G}\) whose girth (odd-girth) is greater than \(g^*\) admits a homomorphism to the five cycle (i.e. is \(\mathrm {C}_{_{5}}\)-colourable). Although, the question “Is the class of simple 3-regular graphs pentagonal?” proposed by Ne?et?il (Taiwan J Math 3:381–423, 1999) is still a central open problem, Gebleh (Theorems and computations in circular colourings of graphs, 2007) has shown that there exists an odd-girth-closed subclass of simple 3-regular graphs which is not odd-pentagonal. In this article, motivated by the conjecture that the class of generalized Petersen graphs is odd-pentagonal, we show that finding the odd girth of generalized Petersen graphs can be transformed to an integer programming problem, and using the combinatorial and number theoretic properties of this problem, we explicitly compute the odd girth of such graphs, showing that the class is odd-girth-closed. Also, we obtain upper and lower bounds for the circular chromatic number of these graphs, and as a consequence, we show that the subclass containing generalized Petersen graphs \(\mathrm {Pet}(n,k)\) for which either k is even, n is odd and \(n\mathop {\equiv }\limits ^{k-1}\pm 2\) or both n and k are odd and \(n\ge 5k\) is odd-pentagonal. This in particular shows the existence of nontrivial odd-pentagonal subclasses of 3-regular simple graphs.     

First-Fit colorings of graphs with no cycles of a prescribed even length

The First-Fit (or Grundy) chromatic number of a graph G denoted by \(\chi _{{_\mathsf{FF}}}(G)\), is the maximum number of colors used by the First-Fit (greedy) coloring algorithm when applied to G. In this paper we first show that any graph G contains a bipartite subgraph of Grundy number \(\lfloor \chi _{{_\mathsf{FF}}}(G) /2 \rfloor +1\). Using this result we prove that for every \(t\ge 2\) there exists a real number \(c>0\) such that in every graph G on n vertices and without cycles of length 2t, any First-Fit coloring of G uses at most \(cn^{1/t}\) colors. It is noted that for \(t=2\) this bound is the best possible. A compactness conjecture is also proposed concerning the First-Fit chromatic number involving the even girth of graphs.     

Upper bounds for the total rainbow connection of graphs

A two-agent scheduling problem on parallel machines is considered. Our objective is to minimize the makespan for agent A, subject to an upper bound on the makespan for agent B. When the number of machines, denoted by \(m\), is chosen arbitrarily, we provide an \(O(n)\) algorithm with performance ratio \(2-\frac{1}{m}\), i.e., the makespan for agent A given by the algorithm is no more than \(2-\frac{1}{m}\) times the optimal value, while the makespan for agent B is no more than \(2-\frac{1}{m}\) times the threshold value. This ratio is proved to be tight. Moreover, when \(m=2\), we present an \(O(nlogn)\) algorithm with performance ratio \(\frac{1+\sqrt{17}}{4}\approx 1.28\) which is smaller than \(\frac{3}{2}\). The ratio is weakly tight.     

Paired-domination number of claw-free odd-regular graphs

A paired-dominating set of a graph G is a dominating set of vertices whose induced subgraph has a perfect matching, while the paired-domination number is the minimum cardinality of a paired-dominating set in the graph, denoted by \(\gamma _{pr}(G)\). Let G be a connected \(\{K_{1,3}, K_{4}-e\}\)-free cubic graph of order n. We show that \(\gamma _{pr}(G)\le \frac{10n+6}{27}\) if G is \(C_{4}\)-free and that \(\gamma _{pr}(G)\le \frac{n}{3}+\frac{n+6}{9(\lceil \frac{3}{4}(g_o+1)\rceil +1)}\) if G is \(\{C_{4}, C_{6}, C_{10}, \ldots , C_{2g_o}\}\)-free for an odd integer \(g_o\ge 3\); the extremal graphs are characterized; we also show that if G is a 2 -connected, \(\gamma _{pr}(G) = \frac{n}{3} \). Furthermore, if G is a connected \((2k+1)\)-regular \(\{K_{1,3}, K_4-e\}\)-free graph of order n, then \(\gamma _{pr}(G)\le \frac{n}{k+1} \), with equality if and only if \(G=L(F)\), where \(F\cong K_{1, 2k+2}\), or k is even and \(F\cong K_{k+1,k+2}\).     

Approximation for maximizing monotone non-decreasing set functions with a greedy method

We study the problem of maximizing a monotone non-decreasing function \(f\) subject to a matroid constraint. Fisher, Nemhauser and Wolsey have shown that, if \(f\) is submodular, the greedy algorithm will find a solution with value at least \(\frac{1}{2}\) of the optimal value under a general matroid constraint and at least \(1-\frac{1}{e}\) of the optimal value under a uniform matroid \((\mathcal {M} = (X,\mathcal {I})\), \(\mathcal {I} = \{ S \subseteq X: |S| \le k\}\)) constraint. In this paper, we show that the greedy algorithm can find a solution with value at least \(\frac{1}{1+\mu }\) of the optimum value for a general monotone non-decreasing function with a general matroid constraint, where \(\mu = \alpha \), if \(0 \le \alpha \le 1\); \(\mu = \frac{\alpha ^K(1-\alpha ^K)}{K(1-\alpha )}\) if \(\alpha > 1\); here \(\alpha \) is a constant representing the “elemental curvature” of \(f\), and \(K\) is the cardinality of the largest maximal independent sets. We also show that the greedy algorithm can achieve a \(1 - (\frac{\alpha + \cdots + \alpha ^{k-1}}{1+\alpha + \cdots + \alpha ^{k-1}})^k\) approximation under a uniform matroid constraint. Under this unified \(\alpha \)-classification, submodular functions arise as the special case \(0 \le \alpha \le 1\).     

On zero-sum $$\mathbb {Z}_{2j}^k$$-magic graphs

Let \(G = (V,E)\) be a finite graph and let \((\mathbb {A},+)\) be an abelian group with identity 0. Then G is \(\mathbb {A}\)-magic if and only if there exists a function \(\phi \) from E into \(\mathbb {A} - \{0\}\) such that for some \(c \in \mathbb {A}, \sum _{e \in E(v)} \phi (e) = c\) for every \(v \in V\), where E(v) is the set of edges incident to v. Additionally, G is zero-sum \(\mathbb {A}\)-magic if and only if \(\phi \) exists such that \(c = 0\). We consider zero-sum \(\mathbb {A}\)-magic labelings of graphs, with particular attention given to \(\mathbb {A} = \mathbb {Z}_{2j}^k\). For \(j \ge 1\), let \(\zeta _{2j}(G)\) be the smallest positive integer c such that G is zero-sum \(\mathbb {Z}_{2j}^c\)-magic if c exists; infinity otherwise. We establish upper bounds on \(\zeta _{2j}(G)\) when \(\zeta _{2j}(G)\) is finite, and show that \(\zeta _{2j}(G)\) is finite for all r-regular \(G, r \ge 2\). Appealing to classical results on the factors of cubic graphs, we prove that \(\zeta _4(G) \le 2\) for a cubic graph G, with equality if and only if G has no 1-factor. We discuss the problem of classifying cubic graphs according to the collection of finite abelian groups for which they are zero-sum group-magic.     

Semi-online scheduling on two uniform machines with the known largest size

This paper investigates semi-online scheduling on two uniform machines with the known largest size. Denote by s _j the speed of each machine, j=1,2. Assume 0<s ₁≤s ₂, and let s=s ₂/s ₁ be the speed ratio. First, for the speed ratio \(s\in [1,\sqrt{2}]\), we present an optimal semi-online algorithm \(\mathcal{LSMP}\) with the competitive ratio \(\mathrm{max}\{\frac {2(s+1)}{2s+1},s\}\). Second, we present a semi-online algorithm \(\mathcal{HSMP}\). And for \(s\in(\sqrt{2},1+\sqrt{3})\), the competitive ratio of \(\mathcal{HSMP}\) is strictly smaller than that of the online algorithm \(\mathcal{LS}\). Finally, for the speed ratio s≥s ^*≈3.715, we show that the known largest size cannot help us to design a semi-online algorithm with the competitive ratio strictly smaller than that of \(\mathcal{LS}\). Moreover, we show a lower bound for \(s\in(\sqrt{2},s^{*})\).     

Online tradeoff scheduling on a single machine to minimize makespan and maximum lateness

In this paper, we consider the following single machine online tradeoff scheduling problem. A set of n independent jobs arrive online over time. Each job \(J_{j}\) has a release date \(r_{j}\), a processing time \(p_{j}\) and a delivery time \(q_{j}\). The characteristics of a job are unknown until it arrives. The goal is to find a schedule that minimizes the makespan \(C_{\max } = \max _{1 \le j \le n} C_{j}\) and the maximum lateness \(L_{\max } = \max _{1 \le j \le n} L_{j}\), where \(L_{j} = C_{j} + q_{j}\). For the problem, we present a nondominated \(( \rho , 1 + \displaystyle \frac{1}{\rho } )\)-competitive online algorithm for each \(\rho \) with \( 1 \le \rho \le \displaystyle \frac{\sqrt{5} + 1}{2}\).     

A quadratic time exact algorithm for continuous connected 2-facility location problem in trees

This paper studies the continuous connected 2-facility location problem (CC2FLP) in trees. Let \(T = (V, E, c, d, \ell , \mu )\) be an undirected rooted tree, where each node \(v \in V\) has a weight \(d(v) \ge 0\) denoting the demand amount of v as well as a weight \(\ell (v) \ge 0\) denoting the cost of opening a facility at v, and each edge \(e \in E\) has a weight \(c(e) \ge 0\) denoting the cost on e and is associated with a function \(\mu (e,t) \ge 0\) denoting the cost of opening a facility at a point x(e, t) on e where t is a continuous variable on e. Given a subset \(\mathcal {D} \subseteq V\) of clients, and a subset \(\mathcal {F} \subseteq \mathcal {P}(T)\) of continuum points admitting facilities where \(\mathcal {P}(T)\) is the set of all the points on edges of T, when two facilities are installed at a pair of continuum points \(x_1\) and \(x_2\) in \(\mathcal {F}\), the total cost involved in CC2FLP includes three parts: the cost of opening two facilities at \(x_1\) and \(x_2\), K times the cost of connecting \(x_1\) and \(x_2\), and the cost of all the clients in \(\mathcal {D}\) connecting to some facility. The objective is to open two facilities at a pair of continuum points in \(\mathcal {F}\) to minimize the total cost, for a given input parameter \(K \ge 1\). This paper focuses on the case of \(\mathcal {D} = V\) and \(\mathcal {F} = \mathcal {P}(T)\). We first study the discrete version of CC2FLP, named the discrete connected 2-facility location problem (DC2FLP), where two facilities are restricted to the nodes of T, and devise a quadratic time edge-splitting algorithm for DC2FLP. Furthermore, we prove that CC2FLP is almost equivalent to DC2FLP in trees, and develop a quadratic time exact algorithm based on the edge-splitting algorithm. Finally, we adapt our algorithms to the general case of \(\mathcal {D} \subseteq V\) and \(\mathcal {F} \subseteq \mathcal {P}(T)\).