The Software for Constructing Trails with Local Restrictions in Graphs ()

Tatyana Panyukova, Igor Alferov

Department of Mathematical Methods in Economics and Statistics, South Ural State University, Chelyabinsk, Russian Federation.

**DOI: **10.4236/ojdm.2013.32017
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Department of Mathematical Methods in Economics and Statistics, South Ural State University, Chelyabinsk, Russian Federation.

The present research considers the problem of covering a
graph with minimal number of trails satisfying the pre-defined local
restrictions. The research is
devoted to the problem of graph covering by minimal number of trails satisfying
some local restrictions. Algotithm of allowed Eulerian cycle construction is
considered. The authors showed that it is possible to
recognize the system of transitions and solve the problem of constructing the
allowable path by linear time. It’s also possible to find allowable Eulerian
cycle for Eulerian graph or to proclaim that such a cycle does not exist by the
time O(｜V(G)｜^{.}｜E(G)｜). All presented algorithms have the software realization.

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Panyukova, T. and Alferov, I. (2013) The Software for Constructing Trails with Local Restrictions in Graphs. *Open Journal of Discrete Mathematics*, **3**, 86-92. doi: 10.4236/ojdm.2013.32017.

1. Introduction

Lots of problems of finding paths satisfying the different restrictions can be applied to some practical problems. For example for sheet material cutting problem plane graph represents the model of cutting plan, and a path covering all its edges defines the trajectory of cutter. The restriction defined for this problem is lack of intersection of any initial part of path with edges that are not passed yet [1]. Creating the control systems using non-oriented graphs the following problems of constructing the paths with different restrictions can arise. Among them are straight-ahead paths [2]; paths the next edge of which is defined by the given cyclic order on the set of incident edges [3-5]; paths for which it’s necessary to pass some edges in pre-defined order [5].

The restrictions on the order of vertices and edges can be classified as local (the next edge of a path is defined by conditions established at the current vertex or edge [2-8]), and global (Eulerian, Hamiltonian cycles, bidirectional double tracing etc.). Most of researches are devoted to algorithms with local restrictions of edges order in a path. The present research considers the problem of covering a graph with minimal number of trails satisfying the pre-defined local restrictions.

2. Constructing of T_{G}-Compatible Path

The generalization of most of particular cases for problem of simple trail with local restrictions construction and analysis of its computing complexity is made by S.Szeider [7].

Let’s quote the basic definitions and results of this research to make the further statements clear. Let’s confine with finite simple graphs. Let’s designate as and the sets of vertices and edges of graph G correspondingly. For vertex let’s define the set of all graph G edges incident to vertex v. The degree of vertex v let be designated as; for let. Let if H be vertex-induced subgraph of graph G i.e. the subgraph received of graph G by deleting of one set of vertices and only all edges incident to vertices of this set.

Restrictions for paths in graph G can be defined in terms of allowed transitions graph.

Definition 1. Let transition graph for vertex be a graph vertices of which are the edges incident to vertex v i.e., and set of edges consists of allowed transitions.

Definition 2. The system of allowed transitions (or shortly, system of transitions) is called the set where be the transition graph for vertex v.

Definition 3. The path for graph G is called -compatible if for each i.

Theorem 1 [S. Szeider]. If all graphs of transitions belong either class M of full multipartite graphs or class P of matchings then the problem of -compatible trail constructing can be solved by the time. Otherwise this problem is NP-complete.

If the system of transitions for a vertex is a matching then this problem can be reduced to the problem for graph

,

If for any vertex graph is full multipartite graph then a trail can be constructed by the following algorithm.

Algorithm -Compatible Path

• Input:

• Graph;

• Vertices x, y the end-vertices of -compatible trail;

• System of transitions:.

• Output:

• The sequence of edges corresponding to -compatible trail between vertices x and y or the message that such a path does not exist.

Step 1. If vertex x or vertex y is isolated then stop: path does not exist.

Step 2. Delete all isolated vertices from graph G.

Step 3. Construct the supplementary graph as following (figure 1):

• Each vertex should be split into vertices where be the number of parts of graph. The edges of corresponding part of graph and one additional vertex are incident to vertex;

• Add two new vertices and, edge, and edge for each part of graph,.

Step 4. Construct the initial matching for graph

.

Figure 1. Illustration how supplementary graph is constructed.

Step 5. Find the alternate sequence between vertices x and y that enlarges the cardinality of matching for graph. If it’s impossible to find such a sequence then stop (matching has maximal cardinality and graph has no -compatible path). Otherwise all the edges of found enlarging path except of additional edges of graph produce the -compatible path between vertices x and y. Stop.

Let’s admit that there is open question in research [7]. This question is about recognition the multipartiteness of graphs. Problems of constructing the allowed path or set of paths covering all the edges of given graph are not also considered.

Let’s illustrate an example of graph G (figure 2) that algorithm -COMPATIBLE PATH cannot be used for constructing of paths covering all edges of graph G. Let the following system of transitions is defined for the graph:

, , , , , , , , , , , , , , ,.

Supplementary graph for finding of -compatible path between vertices and which construction is reviewed on step 3 of algorithm is shown at figure 3.

The initial matching is marked by thick lines. The alternate enlarging sequence of edges for this matching be

, , , , , , , , , , , ,.

Edges of this sequence not belonging the initial matching are represented by dash line. These edges form the set

Figure 2. Example of graph.

Figure 3. Graph G' received of graph G by additional constructions.

, , , , , ,.

All edges of this set belonging to graph G i.e., form -compatible path from vertex to vertex.

Using algorithm -COMPATIBLE PATH it’s possible to construct only a simple trail between two different vertices (i.e. a trail where each vertex is presented only once).

Figure 4 shows the software realization of the represented algorithm. The bold line marks the found trail between vertices 1 and 4. This trail corresponds the system

Conflicts of Interest

The authors declare no conflicts of interest.

[1] | T. Panyukova, “Cover with Ordered Enclosing for Flat Graphs,” Electronic Notes in Discrete Mathematics, Vol. 28, 2007, pp. 17-24. doi:10.1016/j.endm.2007.01.004 |

[2] | T. Pisanski, T. W. Tucker and A. Zitnik, “Straight-Ahead walks in Eulerian Graphs,” Discrete Mathematics, Vol. 281, No. 1-3, 2004, pp. 237-246. doi:10.1016/j.disc.2003.09.011 |

[3] | H. Fleischner, “Eulerian Graphs and Related Topics,” Part 1, Vol. 1, Elsevier, Amsterdam, 1990. |

[4] | H. Fleischner, “Eulerian Graphs and Related Topics,” Part 1, Vol. 2, Elsevier, Amsterdam, 1991. |

[5] | H. Fleischner, L. W. Beineke and R. J. Wilson, “Eulerian Graphs, Selected Topics in Graph Theory 2,” Academic Press, London, New York, 1983, pp. 17-53. |

[6] | D. Chebikin, “On k-Edge-Ordered Graphs,” Discrete Mathematics, Vol. 281, No. 1-3, 2004, pp. 115-128. doi:10.1016/j.disc.2003.09.004 |

[7] | S. Szeider, “Finding Paths in Graphs Avoiding Forbidden Transitions,” Discrete Applied Mathematics, Vol. 126, No. 2-3, 2003, pp. 261-273. doi:10.1016/S0166-218X(02)00251-2 |

[8] | A. Kotzig, “Moves without Forbidden Transitions in a Graph,” Matematicky Casopis, Vol. 18, No. 1, 1968, pp. 76-80. |

[9] | T. A. Panyukova, “The Paths with Local Restrictions,” Reports of South Ural State University. Section: Mathematical Modelling and Programming, Vol. 5, No. 16, 2010, pp. 58-67 (in Russian). |

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