Connected matchings in chordal bipartite graphs

A connected matching in a graph is a collection of edges that are pairwise disjoint but joined by another edge of the graph. Motivated by applications to Hadwiger’s conjecture, Plummer, Stiebitz, and Toft (2003) introduced connected matchings and proved that, given a positive integer $k$, determining whether a graph has a connected matching of size at least $k$ is NP-complete. Cameron (2003) proved that this problem remains NP-complete on bipartite graphs, but can be solved in polynomial-time on chordal graphs. We present a polynomial-time algorithm that finds a maximum connected matching in a chordal bipartite graph. This includes a novel edge-without-vertex-elimination ordering of independent interest. We give several applications of the algorithm, including computing the Hadwiger number of a chordal bipartite graph, solving the unit-time bipartite margin-shop scheduling problem in the case in which the bipartite complement of the precedence graph is chordal bipartite, and determining–in a totally balanced binary matrix–the largest size of a square sub-matrix that is permutation equivalent to a matrix with all zero entries above the main diagonal.     

On coloring problems with local constraints

We show complexity results for some generalizations of the graph coloring problem on two classes of perfect graphs, namely clique trees and unit interval graphs. We deal with the μ-coloring problem (upper bounds for the color on each vertex), the precoloring extension problem (a subset of vertices colored beforehand), and a problem generalizing both of them, the (γ, μ)-coloring problem (lower and upper bounds for the color on each vertex). We characterize the complexity of all those problems on clique trees of different heights, providing polytime algorithms for the cases that are easy. These results have two interesting corollaries: first, one can observe on clique trees of different heights the increasing complexity of the chain k-coloring, μ-coloring, (γ, μ)-coloring, list-coloring. Second, clique trees of height 2 are the first known example of a class of graphs where μ-coloring is polynomial time solvable and precoloring extension is NP-complete, thus being at the same time the first example where μ-coloring is polynomially solvable and (γ, μ)-coloring is NP-complete. Last, we show that the μ-coloring problem on unit interval graphs is NP-complete. These results answer three questions from [Ann. Oper. Res. 169(1) (2009), 3–16].     

On size, order, diameter and minimum degree

Let G be a finite connected graph. We give an asymptotically tight upper bound on the size of G in terms of order, diameter and minimum degree. Our result is a strengthening of an old classical theorem of Ore [Diameters in graphs, J. Combin. Theory, 5 (1968), 75–81] if minimum degree is prescribed and constant.     

General scheduling non-approximability results in presence of hierarchical communications

We investigate on the issue of minimizing the makespan (resp. the sum of the completion times) for the multiprocessor scheduling problem in presence of hierarchical communications. We consider a model with two levels of communication: interprocessor and intercluster. The processors are grouped in fully connected clusters. We propose general non-approximability results in the case where all the tasks of the precedence graph have unit execution times, and where the multiprocessor is composed of an unrestricted number of machines with l ? 4 identical processors each.     

Scheduling groups of tasks with precedence constraints on three dedicated processors

We study the problem of scheduling groups of tasks with precedence constraints on three dedicated processors. Each task requires a specified set of processors. Up to three precedence constraints are considered among groups of tasks requiring the same set of processors. The objective of the problem is to find a nonpreemptive schedule which minimizes the maximum completion time (makespan). This scheduling problem is equivalent to the problem of finding an extension of the constraint graph (i.e. the graph which represents the conflicts between tasks and the precedence constraints) to a comparability graph with minimum (over all the extensions) maximum clique weight. The problem is NP-hard in the strong sense. A normal schedule is such that all the tasks requiring the same set of processors are scheduled consecutively. With a normal schedule the problem reduces to the quotient graph of the constraint graph. In this paper we obtain tight approximation results for the minimum makespan of a normal schedule through tight results on the minimum increase of the maximum clique weight when the (partially oriented) quotient graph is extended to a comparability graph.     

Poset Entropy Versus Number of Linear Extensions: The Width-2 Case

Kahn and Kim (J. Comput. Sci. 51, 3, 390–399, 1995) have shown that for a finite poset P, the entropy of the incomparability graph of P (normalized by multiplying by the order of P) and the base-2 logarithm of the number of linear extensions of P are within constant factors from each other. The tight constant for the upper bound was recently shown to be 2 by Cardinal et al. (Combinatorica 33, 655–697, 2013). Here, we refine this last result in case P has width 2: we show that the constant can be replaced by 2?ε if one also takes into account the number of connected components of size 2 in the incomparability graph of P. Our result leads to a better upper bound for the number of comparisons in algorithms for the problem of sorting under partial information.     

Minimizing makespan for a bipartite graph on a single processor with an integer precedence delay

We consider the makespan minimization for a unit execution time task sequencing problem with a bipartite precedence delays graph and a positive precedence delay d. We prove that the associated decision problem is strongly NP-complete and we provide a non-trivial polynomial sub-case. We also give an approximation algorithm with ratio .     

A 54 algorithm for two-dimensional packing

This paper proposes a new algorithm for a two-dimensional packing problem first studied by Baker, Coffman, and Rivest (SIAM J. Comput.9, No. 4(1980), 846–855). In their model, a finite list of rectangles is to be packed into a rectangular bin of finite width but infinite height. The model has applications to certain scheduling and stock-cutting problems. Since the problem of finding an optimal packing is NP-hard, previous work has been directed at finding polynomial approximation algorithms for the problem, i.e., algorithms which come within a constant times the height used by an optimal packing. For the algorithm proposed in this paper, the ratio of the height obtained by the algorithm and the height used by an optimal packing is asymptotically bounded by $\text{5}\text{4}$. This bound is an improvement over the bound of $\text{4}\text{3}$ achieved by the best previous algorithm.     

Maximization Problems in Single Machine Scheduling

Problems of scheduling n jobs on a single machine to maximize regular objective functions are studied. Precedence constraints may be given on the set of jobs and the jobs may have different release times. Schedules of interest are only those for which the jobs cannot be shifted to start earlier without changing job sequence or violating release times or precedence constraints. Solutions to the maximization problems provide an information about how poorly such schedules can perform. The most general problem of maximizing maximum cost is shown to be reducible to n similar problems of scheduling n?1 jobs available at the same time. It is solved in O(mn+n ²) time, where m is the number of arcs in the precedence graph. When all release times are equal to zero, the problem of maximizing the total weighted completion time or the weighted number of late jobs is equivalent to its minimization counterpart with precedence constraints reversed with respect to the original ones. If there are no precedence constraints, the problem of maximizing arbitrary regular function reduces to n similar problems of scheduling n?1 jobs available at the same time.     

Supereulerian graphs and the Petersen graph

A graphG is supereulerian if G has a spanning eulerian subgraph.Boesch et al.[J.Graph Theory,1,79–84(1977)]proposed the problem of characterizing supereulerian graphs.In this paper,we prove that any 3-edge-connected graph with at most 11 edge-cuts of size 3 is supereulerian if and only if it cannot be contractible to the Petersen graph.This extends a former result of Catlin and Lai[J.Combin.Theory,Ser.B,66,123–139(1996)].     

Task scheduling with and without communication delays: A unified approach

The problem of scheduling directed acyclic task graphs on an unbounded number of processors is considered. We present a single algorithm which is applicable to several special cases, thus effecting a unified approach to task scheduling independent of the task graph. We start by considering multi-stage dags and present an algorithm that computes a schedule in O(Nq log q) time, where N is the number of stages, and q is the maximum number of edges between any two stages of the graph. We show that the schedule produced by the algorithm is optimal when: (i) all communication delays are zero or, (ii) the precedence graph is an in-tree or an out-tree and communication times are small or, (iii) the task graph is densely connected and communication costs and processing costs are unity. For multi-stage dags with small communication times we show that the makespan of the schedule generated by our algorithm is less than twice that of the optimal. We also bound the makespan for the case when communication times are arbitrary. We then show how the algorithm may be applied to schedule arbitrary dags and derive the performance bounds for this case. Finally, we present the results of tests we carried out with randomly generated task graphs. These seem to indicate that, on the average, the algorithm performs substantially better than theoretical worst case predictions.     

Clique-critical graphs: Maximum size and recognition

The clique graph of G, K(G), is the intersection graph of the family of cliques (maximal complete sets) of G. Clique-critical graphs were defined as those whose clique graph changes whenever a vertex is removed. We prove that if G has m edges then any clique-critical graph in K^-1(G) has at most 2m vertices, which solves a question posed by Escalante and Toft [On clique-critical graphs, J. Combin. Theory B 17 (1974) 170-182]. The proof is based on a restatement of their characterization of clique-critical graphs. Moreover, the bound is sharp. We also show that the problem of recognizing clique-critical graphs is NP-complete.     

Mathematical programming models for some smallest-world problems

Given a weighted graph G, in the minimum-cost-edge-selection problem (MCES), a minimum weighted set of edges is chosen subject to an upper bound on the diameter of graph G. Similarly, in the minimum-diameter-edge-selection problem (MDES), a set of edges is chosen to minimize the diameter subject to an upper bound on their total weight. These problems are shown to be equivalent and proven to be NP-complete. MCES is then formulated as a 0–1 integer programming problem. The problems MCES and MDES provide models for determining smallest-world networks and for measuring the “small-worldness” of graphs.     

Preemptive Hybrid Flowshop Scheduling problem of interval orders

The Preemptive Hybrid (multi-processor) Flowshop Scheduling (PHFS) problem consists in preemptively scheduling n jobs in a flowshop subject to precedence constraints with the objective of minimizing the makespan. A special case of the general precedence constraints problems is NP-hard in the strong sense, Hoogeveen et al. [J.A. Hoogeveen, J.K. Lenstra, B. Veltman, European Journal of Operational Research 89 (1996) 172]. In this paper a class of precedence constraints is proposed for which the problem is polynomially solvable. The reported results demonstrate the feasibility and reliability of the proposed approach. This should open future prospects for developing approximation algorithms for any class of precedence constraints.     

Polygon-circle and word-representable graphs

We describe work on the relationship between the independently-studied polygon-circle graphs and word-representable graphs.A graph G = (V, E) is word-representable if there exists a word w over the alpha-bet V such that letters x and y form a subword of the form xyxy ⋯ or yxyx ⋯ iff xy is an edge in E. Word-representable graphs generalise several well-known and well-studied classes of graphs [S. Kitaev, A Comprehensive Introduction to the Theory of Word-Representable Graphs, Lecture Notes in Computer Science 10396 (2017) 36–67; S. Kitaev, V. Lozin, “Words and Graphs”, Springer, 2015]. It is known that any word-representable graph is k-word-representable, that is, can be represented by a word having exactly k copies of each letter for some k dependent on the graph. Recognising whether a graph is word-representable is NP-complete ([S. Kitaev, V. Lozin, “Words and Graphs”, Springer, 2015, Theorem 4.2.15]). A polygon-circle graph (also known as a spider graph) is the intersection graph of a set of polygons inscribed in a circle [M. Koebe, On a new class of intersection graphs, Ann. Discrete Math. (1992) 141–143]. That is, two vertices of a graph are adjacent if their respective polygons have a non-empty intersection, and the set of polygons that correspond to vertices in this way are said to represent the graph. Recognising whether an input graph is a polygon-circle graph is NP-complete [M. Pergel, Recognition of polygon-circle graphs and graphs of interval filaments is NP-complete, Graph-Theoretic Concepts in Computer Science: 33rd Int. Workshop, Lecture Notes in Computer Science, 4769 (2007) 238–247]. We show that neither of these two classes is included in the other one by showing that the word-representable Petersen graph and crown graphs are not polygon-circle, while the non-word-representable wheel graph W₅ is polygon-circle. We also provide a more refined result showing that for any k ≥ 3, there are k-word-representable graphs which are neither (k −1)-word-representable nor polygon-circle.     

A buffer minimization problem for the design of embedded systems

We consider a set of tasks, each of them is composed by a set of sequential operations, and a set of buffers. Each buffer b is defined between two tasks T_i and T_j, and is managed as a FIFO structure. Some operations from T_i write data to the buffer b, others from T_j get data from b.The writings and readings generate precedence constraints between the operations. The limitation of the size of the buffers generates another set of precedence constraints between them and circuits in the precedence graph may appear. In this case, there is no feasible schedule for the operations. The aim is to determine the size of each buffer such that the global surface of the buffers is minimized and there is no circuit in the precedence graph.We prove that this problem is polynomial for two tasks using a flow algorithm. We also prove that it is NP-complete in the strong sense for three tasks.     

Two machine preemptive scheduling problem with release dates,equal processing times and precedence constraints

We consider a scheduling problem with two identical parallel machines and n jobs. For each job we are given its release date when job becomes available for processing. All jobs have equal processing times. Preemptions are allowed. There are precedence constraints between jobs which are given by a (di)graph consisting of a set of outtrees and a number of isolated vertices. The objective is to find a schedule minimizing mean flow time. We suggest an O(n²) algorithm to solve this problem.The suggested algorithm also can be used to solve the related two-machine open shop problem with integer release dates, unit processing times and analogous precedence constraints.     

On Rerouting Connection Requests in Networks with Shared Bandwidth

In this paper, we address the problem of scheduling the switching of a set of connection requests one after the other from current routing to another pre-determined routing. We propose a model that handles requests using only a constant fraction of the bandwidth of a link, thus generalizing the model proposed in [Coudert, D. and J.-S. Sereni, Characterization of graphs and digraphs with small process number, Research Report 6285, INRIA (2007). URL http://hal.inria.fr/inria-00171083/; Jose, N. and A. Somani, Connection rerouting/network reconfiguration, Design of Reliable Communication Networks (2003), pp. 23–30.] for WDM networks. Our main result is the proof that the problem of deciding whether it exists a scheduling of the rerouting of connection requests without traffic interruption is NP-complete even if requests use the third of the bandwidth of a link. Note that the problem is polynomial when the bandwidth of a link cannot be shared [Coudert, D. and J.-S. Sereni, Characterization of graphs and digraphs with small process number, Research Report 6285, INRIA (2007). URL http://hal.inria.fr/inria-00171083/].     

Complexity of scheduling of coupled tasks with chains precedence constraints and any constant length of gap

Coupled tasks scheduling was originally introduced for modelling complex radar devices. It is still used for controlling such devices and applied in similar applications. This paper considers a problem of coupled tasks scheduling on one processor, under the assumptions that all processing times are equal to 1, the gap has a constant exact length and the precedence constraints are strict. Although it is proven that the problem stated above is NP-hard in the strong sense if the precedence constraints have a form of a general graph, it is possible to solve some of its relaxed versions in polynomial time. This paper contains a solution for the problem of coupled tasks scheduling with an assumption that the precedence constraints graph has a form of chains and it presents an algorithm that can solve the problem with such assumption in time O(n?log?n).