A generalized Weiszfeld method for the multi-facility location problem

An iterative method is proposed for the K facilities location problem. The problem is relaxed using probabilistic assignments, depending on the distances to the facilities. The probabilities, that decompose the problem into K single-facility location problems, are updated at each iteration together with the facility locations. The proposed method is a natural generalization of the Weiszfeld method to several facilities.     

The backup 2-median problem on block graphs

The backup 2-median problem is a location problem to locate two facilities at vertices with the minimum expected cost where each facility may fail with a given probability. Once a facility fails, the other one takes full responsibility for the services. Here we assume that the facilities do not fail simultaneously. In this paper, we consider the backup 2-median problem on block graphs where any two edges in one block have the same length and the lengths of edges on different blocks may be different. By constructing a tree-shaped skeleton of a block graph, we devise an O（n log n q- m）-time algorithm to solve this problem where n and m are the number of vertices and edges, respectively, in the given block graph.     

The location of median paths on grid graphs

In this paper we consider the location of a path shaped facility on a grid graph. In the literature this problem was extensively studied on particular classes of graphs as trees or series-parallel graphs. We consider here the problem of finding a path which minimizes the sum of the (shortest) distances from it to the other vertices of the grid, where the path is also subject to an additional constraint that takes the form either of the length of the path or of the cardinality. We study the complexity of these problems and we find two polynomial time algorithms for two special cases, with time complexity of O(n) and O(nℓ) respectively, where n is the number of vertices of the grid and ℓ is the cardinality of the path to be located. The literature about locating dimensional facilities distinguishes between the location of extensive facilities in continuous spaces and network facility location. We will show that the problems presented here have a close connection with continuous dimensional facility problems, so that the procedures provided can also be useful for solving some open problems of dimensional facilities location in the continuous case.     

Planar maximal covering location problem under block norm distance measure

This paper introduces a new model for the planar maximal covering location problem (PMCLP) under different block norms. The problem involves locating g facilities anywhere on the plane in order to cover the maximum number of n given demand points. The generalization, in this paper, is that the distance measures assigned to facilities are block norms of different types and different proximity measures. First, the PMCLP under different block norms is modelled as a maximum clique partition problem on an equivalent multi-interval graph. Then, the equivalent graph problem is modelled as an unconstrained binary quadratic problem (UQP). Both the maximum clique partition problem and the UQP are NP-hard problems; therefore, we solve the UQP format through a genetic algorithm heuristic. Computational examples are given.     

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.     

On a facility location problem with applications to tele-diagnostic

Consider an undirected graph G modelling a network. Each vertex in the graph contains some physical devices, which can be monitored and possibly repaired from a remote site in case they become faulty. We assume that there can be two kinds of faults in the system: soft faults, which can be repaired remotely from another site (i.e., a monitor), and severe faults which cannot be repaired remotely and require further (possibly human) interventions. We assume that soft faults happen with some fixed probability λ, 0 < λ ≤ 1. We investigate the problem of locating monitors in the network so as to minimize the total expected communication cost per fault. We formalize such a problem as a location problem with a cost function depending on λ and study some properties of the optimal solutions. The latter are exploited for investigating the complexity of the problem and providing efficient approximation algorithms.     

Influence Digraphs Induced by Time-Stamped Graphs (Extended Abstract)

A time-stamped graph is an undirected graph with a real number on each edge. Vertex u influences vertex v if there is an increasing path from u to v. The induced influence digraph of a time-stamped graph is the directed graph that records the influences. In this paper we study the realizability problem: Given a parameter value, does there exist a time-stamped graph whose induced influence digraph has the given parameter value? In particular, we solve this problem when the parameter is the number of arcs. Moreover, if the candidates for the time-stamped graphs are restricted to trees, then every realizable value can be achieved by a tree homeomorphic to K₂ or K_1,3. A number of other questions are also explored. The full version of this paper is submitted to a referreed journal.     

Arbitrary decompositions into open and closed trails

The problem of arbitrary decomposition of a graph G into closed trails i.e. a decomposition into closed trails of prescribed lengths summing up to the size of the graph G was first considered in the case of the complete graph G=K_n (for odd n) in connection with vertex-distinguishing coloring of the union of cycles.Next, the same problem was investigated for other families of graphs.In this paper we consider a more general problem: arbitrary decomposition of a graph into open and closed trails. Our results are based on and generalize known results on decomposition of a graph into closed trails. Our results also generalize some results concerning decomposition of a graph into open trails. We here emphasize that the known results on the closed case are basic ingredients for the proof of the open and closed case.     

The p-median problem under uncertainty

Consider the need to currently locate p facilities but it is possible that up to q additional facilities will have to be located in the future. There are known probabilities that 0 ? r ? q facilities will need to be located. The p-median problem under uncertainty is to find the location of p facilities such that the expected value of the objective function in the future is minimized. The problem is formulated on a graph, properties of it are proven, an integer programming formulation is constructed, and heuristic algorithms are suggested for its solution. The heuristic algorithms are modified to reduce the run time by about two orders of magnitude with minimal effect on the quality of the solution. Optimal solutions for many problems are found effectively by CPLEX. Computational results using the heuristic algorithms are presented.     

A note on the m-center problem with rectilinear distances

Given n demand points on a plane, the problem we consider is to locate a given number, m, of facilities on the plane so that the maximum of the set of rectilinear distances of each demand point to its nearest facility is minimized. This problem is known as the m-center problem on the plane. A related problem seeks to determine, for a given r, the minimum number of facilities and their locations so as to ensure that every point is within r units of rectilinear distance from its nearest facility. We formulate the latter problem as a problem of covering nodes by cliques of an intersection graph. Certain bounds are established on the size of the problem. An efficient algorithm is provided to generate this set-covering problem. Computational results with this approach are summarized.     

The realizable extension problem and the weighted graph (K 3,3, l)

This note outlines the realizable extension problem for weighted graphs and provides a detailed analysis of this problem for the weighted graph (K _3,3, l). The main result of this analysis is that the moduli space of planar realizations of (K _3,3, l) can have one, two, four, six or eight connected components and explicit examples of each case are provided. The note culminates with two examples which show that in general, realizability and connectedness results relating to the moduli spaces of weighted cycles which are contained in a larger weighted graph cannot be extended to similar results regarding the moduli space of the larger weighted graph.     

The chain graph sandwich problem

The chain graph sandwich problem asks: Given a vertex set V, a mandatory edge set E ¹, and a larger edge set E ², is there a graph G=(V,E) such that E ¹?E?E ² with G being a chain graph (i.e., a 2K ₂-free bipartite graph)? We prove that the chain graph sandwich problem is NP-complete. This result stands in contrast to (1) the case where E ¹ is a connected graph, which has a linear-time solution, (2) the threshold graph sandwich problem, which has a linear-time solution, and (3) the chain probe graph problem, which has a polynomial-time solution.     

Approximating the fixed linear crossing number

We present a randomized polynomial-time approximation algorithm for the fixed linear crossing number problem (FLCNP). In this problem, the vertices of a graph are placed in a fixed order along a horizontal “node line” in the plane, each edge is drawn as an arc in one of the two half-planes (pages), and the objective is to minimize the number of edge crossings. FLCNP is NP-hard, and no previous polynomial-time approximation algorithms are known. We show that the problem can be generalized to k pages and transformed to the maximum k-cut problem which admits a randomized polynomial-time approximation. For the 2-page case, our approach leads to a randomized polynomial time 0.878+0.122ρ approximation algorithm for FLCNP, where ρ is the ratio of the number of conflicting pairs (pairs of edges that cross if drawn in the same page) to the crossing number. We further investigate this performance ratio on the random graph family G_n,1/2, where each edge of the complete graph K_n occurs with probability . We show that a longstanding conjecture for the crossing number of K_n implies that with probability at least 1-4e^-λ2, the expected performance bound of the algorithm on a random graph from G_n,1/2 is 1.366+O(λ/n). A series of experiments is performed to compare the algorithm against two other leading heuristics on a set of test graphs. The results indicate that the randomized algorithm yields near-optimal solutions and outperforms the other heuristics overall.     

Minimal non-1-planar graphs

A graph is 1-planar if it can be drawn on the plane so that each edge is crossed by no more than one other edge. A non-1-planar graph G is minimal if the graph G-e is 1-planar for every edge e of G. We prove that there are infinitely many minimal non-1-planar graphs (MN-graphs). It is known that every 6-vertex graph is 1-planar. We show that the graph K₇-K₃ is the unique 7-vertex MN-graph.     

A contribution to queens graphs: A substitution method

A graph G is a queens graph if the vertices of G can be mapped to queens on the chessboard such that two vertices are adjacent if and only if the corresponding queens attack each other, i.e. they are in horizontal, vertical or diagonal position.We prove a conjecture of Beineke, Broere and Henning that the Cartesian product of an odd cycle and a path is a queens graph. We show that the same does not hold for two odd cycles. The representation of the Cartesian product of an odd cycle and an even cycle remains an open problem.We also prove constructively that any finite subgraph of the rectangular grid or the hexagonal grid is a queens graph.Using a small computer search we solve another conjecture of the authors mentioned above, saying that K_3,4 minus an edge is a minimal non-queens graph.     

Facility location for market capture when users rank facilities by shorter travel and waiting times

A firm wants to locate several multi-server facilities in a region where there is already a competitor operating. We propose a model for locating these facilities in such a way as to maximize market capture by the entering firm, when customers choose the facilities they patronize, by the travel time to the facility and the waiting time at the facility. Each customer can obtain the service or goods from several (rather than only one) facilities, according to a probabilistic distribution. We show that in these conditions, there is demand equilibrium, and we design an ad hoc heuristic to solve the problem, since finding the solution to the model involves finding the demand equilibrium given by a nonlinear equation. We show that by using our heuristic, the locations are better than those obtained by utilizing several other methods, including MAXCAP, p-median and location on the nodes with the largest demand.     

Edge decompositions into two kinds of graphs

Let H be an arbitrary graph and let K_1,2 be the 2-edge star. By a {K_1,2,H}-decomposition of a graph G we mean a partition of the edge set of G into subsets inducing subgraphs isomorphic to K_1,2 or H. Let J be an arbitrary connected graph of odd size. We show that the problem to decide if an instance graph G has a {K_1,2,H}-decomposition is NP-complete if H has a component of an odd size and H≠pK_1,2∪qJ, where pK_1,2∪qJ is the disjoint union of p copies of K_1,2 and q copies of J. Moreover, we prove polynomiality of this problem for H=qJ.     

Optimal implementation of selectors in a data-base

The records of a data base can be accessed from other records or from a set of data items (inverted access, primary and secondary index of IMS, search keys of CODASYL etc.) which we call selectors. The implementation of this selectors can use different techniques as hash coding, inverted lists or hierarchical index (indexed sequential, B-trees etc…) We consider here the last one and we search for a given set of selectors an optimal index structure. We show how this problem can be put as the search of an optimal rooted tree among the partial subgraphs of a given graph G (this problem is known in graph theory as Steiner problem) and we give several properties which allow the graph G to be notabily reduced. Then we present a branch and bound algorithm to solve this problem.     

splitting number is NP-complete

We consider two graph invariants that are used as a measure of nonplanarity: the splitting number of a graph and the size of a maximum planar subgraph. The splitting number of a graph G is the smallest integer k⩾0, such that a planar graph can be obtained from G by k splitting operations. Such operation replaces a vertex v by two nonadjacent vertices v₁ and v₂, and attaches the neighbors of v either to v₁ or to v₂. We prove that the splitting number decision problem is NP-complete when restricted to cubic graphs. We obtain as a consequence that planar subgraph remains NP-complete when restricted to cubic graphs. Note that NP-completeness for cubic graphs implies NP-completeness for graphs not containing a subdivision of K₅ as a subgraph.     

Minimal 2-matching-covered graphs

A perfect 2-matching M of a graph G is a spanning subgraph of G such that each component of M is either an edge or a cycle. A graph G is said to be 2-matching-covered if every edge of G lies in some perfect 2-matching of G. A 2-matching-covered graph is equivalent to a “regularizable” graph, which was introduced and studied by Berge. A Tutte-type characterization for 2-matching-covered graph was given by Berge. A 2-matching-covered graph is minimal if G−e is not 2-matching-covered for all edges e of G. We use Berge’s theorem to prove that the minimum degree of a minimal 2-matching-covered graph other than K₂ and K₄ is 2 and to prove that a minimal 2-matching-covered graph other than K₄ cannot contain a complete subgraph with at least 4 vertices.