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Francisco J. Soulignac

Publications and source records attributed to Francisco J. Soulignac.

15 recordsLinked to original sources
arXiv2026

The Time-Dependent Traveling Salesman Problem with Loose Time Windows

The time-dependent traveling salesman problem with time windows (TDTSPTW) generalizes the well-known traveling salesman problem with time windows by accounting the effects of congestion on travel times. In this paper, we develop an exact framework for the TDTSPTW with a makespan objective that extends the range of instances solvable to optimality under loose time windows while remaining effective across all levels of time-window tightness. Our framework relies on a dynamic-programming labeling algorithm and combines column generation, ng-memory augmentation, and exact search, using completion bounds for state-space sparsification, variable fixing, and exact search pruning. Embedded within a branch-and-price method, the framework solves all instances with up to 45 customers in a benchmark comprising more than 10,000 instances, including all instances without time windows with up to 50 customers.

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arXiv2026

Beware of the Classical Benchmark Instances for the Traveling Salesman Problem with Time Windows

We propose a simple and exact method for the Traveling Salesman Problem with Time Windows and Makespan objective (\TSPTW-M) that solves all instances of the classical benchmark with $50$ or more customers in less than ten seconds each. Applying this algorithm as an off-the-shelf method, we also solve all but one of these instances for the Duration objective. Our main conclusion is that these instances alone are no longer representative for evaluating the TSPTW-M and its Duration variant: their structure can be exploited to yield results that seem outstanding at first glance. Additionally, caution is advised when designing hard training sets for machine learning algorithms.

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arXiv2018

Total 2-domination of proper interval graphs

A set of vertices $W$ of a graph $G$ is a total $k$-dominating set when every vertex of $G$ has at least $k$ neighbors in $W$. In a recent article, Chiarelli et al.\ (Improved Algorithms for $k$-Domination and Total $k$-Domination in Proper Interval Graphs, Lecture Notes in Comput.\ Sci.\ 10856, 290--302, 2018) prove that a total $k$-dominating set can be computed in $O(n^{3k})$ time when $G$ is a proper interval graph with $n$ vertices and $m$ edges. In this note we reduce the time complexity to $O(m)$ for $k=2$.

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arXiv2018

The eternal dominating set problem for interval graphs

We prove that, in games in which all the guards move at the same turn, the eternal domination and the clique-connected cover numbers coincide for interval graphs. A linear algorithm for the eternal dominating set problem is obtained as a by-product.

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arXiv2017

Minimal and minimum unit circular-arc models

A proper circular-arc (PCA) model is a pair ${\cal M} = (C, \cal A)$ where $C$ is a circle and $\cal A$ is a family of inclusion-free arcs on $C$ in which no two arcs of $\cal A$ cover $C$. A PCA model $\cal U = (C,\cal A)$ is a $(c, \ell)$-CA model when $C$ has circumference $c$, all the arcs in $\cal A$ have length $\ell$, and all the extremes of the arcs in $\cal A$ are at a distance at least $1$. If $c \leq c'$ and $\ell \leq \ell'$ for every $(c', \ell')$-CA model equivalent (resp. isomorphic) to $\cal U$, then $\cal U$ is minimal (resp. minimum). In this article we prove that every PCA model is isomorphic to a minimum model. Our main tool is a new characterization of those PCA models that are equivalent to $(c,\ell)$-CA models, that allows us to conclude that $c$ and $\ell$ are integer when $\cal U$ is minimal. As a consequence, we obtain an $O(n^3)$ time and $O(n^2)$ space algorithm to solve the minimal representation problem, while we prove that the minimum representation problem is NP-complete.

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arXiv2015

A certifying and dynamic algorithm for the recognition of proper circular-arc graphs

We present a dynamic algorithm for the recognition of proper circular-arc (PCA) graphs, that supports the insertion and removal of vertices (together with its incident edges). The main feature of the algorithm is that it outputs a minimally non-PCA induced subgraph when the insertion of a vertex fails. Each operation cost $O(\log n + d)$ time, where $n$ is the number vertices and $d$ is the degree of the modified vertex. When removals are disallowed, each insertion is processed in $O(d)$ time. The algorithm also provides two constant-time operations to query if the dynamic graph is proper Helly (PHCA) or proper interval (PIG). When the dynamic graph is not PHCA (resp. PIG), a minimally non-PHCA (resp. non-PIG) induced subgraph is obtained.

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arXiv2014

Bounded, minimal, and short representations of unit interval and unit circular-arc graphs

We consider the unrestricted, minimal, and bounded representation problems for unit interval (UIG) and unit circular-arc (UCA) graphs. In the unrestricted version, a proper circular-arc (PCA) model $\cal M$ is given and the goal is to obtain an equivalent UCA model $\cal U$. We show a linear time algorithm with negative certification that can also be implemented to run in logspace. In the bounded version, $\cal M$ is given together with some lower and upper bounds that the beginning points of $\cal U$ must satisfy. We develop a linear space $O(n^2)$ time algorithm for this problem. Finally, in the minimal version, the circumference of the circle and the length of the arcs in $\cal U$ must be simultaneously as minimum as possible. We prove that every UCA graph admits such a minimal model, and give a polynomial time algorithm to find it. We also consider the minimal representation problem for UIG graphs. As a bad result, we show that the previous linear time algorithm fails to provide a minimal model for some input graphs. We fix this algorithm but, unfortunately, it runs in linear space $O(n^2)$ time. Finally, we apply the minimal representation algorithms so as to find the minimum powers of paths and cycles that contain a given UIG and UCA models, respectively.

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arXiv2014

Disimplicial arcs, transitive vertices, and disimplicial eliminations

In this article we deal with the problems of finding the disimplicial arcs of a digraph and recognizing some interesting graph classes defined by their existence. A diclique of a digraph is a pair $V \to W$ of sets of vertices such that $v \to w$ is an arc for every $v \in V$ and $w \in W$. An arc $v \to w$ is disimplicial when $N^-(w) \to N^+(v)$ is a diclique. We show that the problem of finding the disimplicial arcs is equivalent, in terms of time and space complexity, to that of locating the transitive vertices. As a result, an efficient algorithm to find the bisimplicial edges of bipartite graphs is obtained. Then, we develop simple algorithms to build disimplicial elimination schemes, which can be used to generate bisimplicial elimination schemes for bipartite graphs. Finally, we study two classes related to perfect disimplicial elimination digraphs, namely weakly diclique irreducible digraphs and diclique irreducible digraphs. The former class is associated to finite posets, while the latter corresponds to dedekind complete finite posets.

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arXiv2012

The star and biclique coloring and choosability problems

A biclique of a graph G is an induced complete bipartite graph. A star of G is a biclique contained in the closed neighborhood of a vertex. A star (biclique) k-coloring of G is a k-coloring of G that contains no monochromatic maximal stars (bicliques). Similarly, for a list assignment L of G, a star (biclique) L-coloring is an L-coloring of G in which no maximal star (biclique) is monochromatic. If G admits a star (biclique) L-coloring for every k-list assignment L, then G is said to be star (biclique) k-choosable. In this article we study the computational complexity of the star and biclique coloring and choosability problems. Specifically, we prove that the star (biclique) k-coloring and k-choosability problems are Σ_2^p-complete and Π_3^p-complete for k > 2, respectively, even when the input graph contains no induced C_4 or K_{k+2}. Then, we study all these problems in some related classes of graphs, including H-free graphs for every H on three vertices, graphs with restricted diamonds, split graphs, threshold graphs, and net-free block graphs.

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arXiv2012

Isomorphism of graph classes related to the circular-ones property

We give a linear-time algorithm that checks for isomorphism between two 0-1 matrices that obey the circular-ones property. This algorithm leads to linear-time isomorphism algorithms for related graph classes, including Helly circular-arc graphs, Γ-circular-arc graphs, proper circular-arc graphs and convex-round graphs.

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arXiv2011

Fully dynamic recognition of proper circular-arc graphs

We present a fully dynamic algorithm for the recognition of proper circular-arc (PCA) graphs. The allowed operations on the graph involve the insertion and removal of vertices (together with its incident edges) or edges. Edge operations cost O(log n) time, where n is the number of vertices of the graph, while vertex operations cost O(log n + d) time, where d is the degree of the modified vertex. We also show incremental and decremental algorithms that work in O(1) time per inserted or removed edge. As part of our algorithm, fully dynamic connectivity and co-connectivity algorithms that work in O(log n) time per operation are obtained. Also, an O(Δ) time algorithm for determining if a PCA representation corresponds to a co-bipartite graph is provided, where Δ is the maximum among the degrees of the vertices. When the graph is co-bipartite, a co-bipartition of each of its co-components is obtained within the same amount of time.

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arXiv2011

Subclasses of Normal Helly Circular-Arc Graphs

A Helly circular-arc model M = (C,A) is a circle C together with a Helly family \A of arcs of C. If no arc is contained in any other, then M is a proper Helly circular-arc model, if every arc has the same length, then M is a unit Helly circular-arc model, and if there are no two arcs covering the circle, then M is a normal Helly circular-arc model. A Helly (resp. proper Helly, unit Helly, normal Helly) circular-arc graph is the intersection graph of the arcs of a Helly (resp. proper Helly, unit Helly, normal Helly) circular-arc model. In this article we study these subclasses of Helly circular-arc graphs. We show natural generalizations of several properties of (proper) interval graphs that hold for some of these Helly circular-arc subclasses. Next, we describe characterizations for the subclasses of Helly circular-arc graphs, including forbidden induced subgraphs characterizations. These characterizations lead to efficient algorithms for recognizing graphs within these classes. Finally, we show how do these classes of graphs relate with straight and round digraphs.

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arXiv2011

Hereditary biclique-Helly graphs: recognition and maximal biclique enumeration

A biclique is a set of vertices that induce a bipartite complete graph. A graph G is biclique-Helly when its family of maximal bicliques satisfies the Helly property. If every induced subgraph of G is also biclique-Helly, then G is hereditary biclique-Helly. A graph is C_4-dominated when every cycle of length 4 contains a vertex that is dominated by the vertex of the cycle that is not adjacent to it. In this paper we show that the class of hereditary biclique-Helly graphs is formed precisely by those C_4-dominated graphs that contain no triangles and no induced cycles of length either 5, or 6. Using this characterization, we develop an algorithm for recognizing hereditary biclique-Helly graphs in O(n^2+αm) time and O(m) space. (Here n, m, and α= O(m^{1/2}) are the number of vertices and edges, and the arboricity of the graph, respectively.) As a subprocedure, we show how to recognize those C_4-dominated graphs that contain no triangles in O(αm) time and O(m) space. Finally, we show how to enumerate all the maximal bicliques of a C_4-dominated graph with no triangles in O(n^2 + αm) time and O(αm) space, and we discuss how some biclique problems can be solved in O(αm) time and O(n+m) space.

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arXiv2010

Arboricity, h-Index, and Dynamic Algorithms

In this paper we present a modification of a technique by Chiba and Nishizeki [Chiba and Nishizeki: Arboricity and Subgraph Listing Algorithms, SIAM J. Comput. 14(1), pp. 210--223 (1985)]. Based on it, we design a data structure suitable for dynamic graph algorithms. We employ the data structure to formulate new algorithms for several problems, including counting subgraphs of four vertices, recognition of diamond-free graphs, cop-win graphs and strongly chordal graphs, among others. We improve the time complexity for graphs with low arboricity or h-index.

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