Construction of weavings in the plane

This work develops, in graph-theoretic terms, a methodology for systematically constructing weavings of overlapping nets derived from 2-colorings of the plane. From a 2-coloring, two disjoint simple, connected graphs called nets are constructed. The union of these nets forms an overlapping net, and a weaving map is defined on the intersection points of the overlapping net to form a weaving. Furthermore, a procedure is given for the construction of mixed overlapping nets and for deriving weavings from them

Sigma chromatic number of graph coronas involving complete graphs

Let c : V(G) → be a coloring of the vertices in a graph G. For a vertex u in G, the color sum of u, denoted by σ(u), is the sum of the colors of the neighbors of u. The coloring c is called a sigma coloring of G if σ(u) ≠ σ(v) whenever u and v are adjacent vertices in G. The minimum number of colors that can be used in a sigma coloring of G is called the sigma chromatic number of G and is denoted by σ(G). Given two simple, connected graphs G and H, the corona of G and H, denoted by G ⊙ H, is the graph obtained by taking one copy of G and |V(G)| copies of H and where the ith vertex of G is adjacent to every vertex of the ith copy of H. In this study, we will show that for a graph G with |V(G)| ≥ 2, and a complete graph Kn of order n, n ≤ σ(G ⊙ Kn ) ≤ max {σ(G), n}. In addition, let Pn and Cn denote a path and a cycle of order n respectively. If m, n ≥ 3, we will prove that σ(Km ⊙ Pn ) = 2 if and only if . If n is even, we show that σ(Km ⊙ Cn ) = 2 if and only if . Furthermore, in the case that n is odd, we show that σ(Km ⊙ Cn ) = 3 if and only if where H(r, s) denotes the number of lattice points in the convex hull of points on the plane determined by the integer parameters r and s

Sigma chromatic numbers of the middle graph of some families of graphs

Let G be a nontrivial connected graph and let c : V (G) → be a vertex coloring of G, where adjacent vertices may have the same color. For a vertex υ of G, the color sum σ(υ) of υ is the sum of the colors of the vertices adjacent to υ. The coloring c is said to be a sigma coloring of G if σ(u) ≠ σ(υ) whenever u and υ are adjacent vertices in G. The minimum number of colors that can be used in a sigma coloring of G is called the sigma chromatic number of G and is denoted by σ(G). In this study, we investigate sigma coloring in relation to a unary graph operation called middle graph. We will show that the sigma chromatic number of the middle graph of any path, cycle, sunlet graph, tadpole graph, ladder graph, or triangular snake graph is 2 except for some small cases. We also determine the sigma chromatic number of the middle graph of stars

On the set chromatic number of the join and comb product of graphs

A vertex coloring c : V(G) → of a non-trivial connected graph G is called a set coloring if NC(u) ≠ NC(v) for any pair of adjacent vertices u and v. Here, NC(x) denotes the set of colors assigned to vertices adjacent to x. The set chromatic number of G, denoted by χs (G), is defined as the fewest number of colors needed to construct a set coloring of G. In this paper, we study the set chromatic number in relation to two graph operations: join and comb prdocut. We determine the set chromatic number of wheels and the join of a bipartite graph and a cycle, the join of two cycles, the join of a complete graph and a bipartite graph, and the join of two bipartite graphs. Moreover, we determine the set chromatic number of the comb product of a complete graph with paths, cycles, and large star graphs

A Zero-Suppressed Binary Decision Diagram Approach for Constrained Path Enumeration

Combinatorial optimization over graphs has been the subject of research. Recently, the solution of such problems by enumeration using a compact data structure called the zero-suppressed binary decision diagram was proposed and studied. The paper augments the existing frontier-based search method of construction and puts forth a technique for accommodating additional constraints during computation. The shortest and longest path problems for the Osaka Metro transit network are simultaneously solved as demonstration. Furthermore, a comparison of the approach with a conventional integer programming method is presented towards justifying the effectiveness of the algorithm

On the Sigma Value and Sigma Range of the Join of a Finite Number of Even Cycles of the Same Order

Let c be a vertex coloring of a simple; connected graph G that uses positive integers for colors. For a vertex v of G; the color sum of v is the sum of the colors of the neighbors of v. If no two adjacent vertices of G have the same color sum; then c is called a sigma coloring of G. The sigma chromatic number of G is the minimum number of colors required in a sigma coloring of G. Let max(c) be the largest color assigned to a vertex of G by a coloring c. The sigma value of G is the minimum value of max(c) over all sigma k−colorings c of G where k is the sigma chromatic number of G. On the other hand; the sigma range of G is the minimum value of max(c) over all sigma colorings c of G. In this paper; we determine the sigma value and the sigma range of the join of a finite number of even cycles of the same order

The Relative Isolation Probability of a Vertex in a Multiple-Source Edge-Weighted Graph

Various measures that characterize graphs exist in literature. Insights into the properties of a graph as a whole and its components are revealed largely through graph measures, also called graph metrics. In seeking to interpret a consequential edge metric from a vertex-centric perspective, the paper advances an original measure – the relative isolation probability of a vertex. Concisely, the probability of relative isolation pertains to the likelihood of a vertex to be disconnected from all designated source vertices in a graph with probability-weighted edges. A two-step algorithm for efficient calculation is presented and evaluated. Contained within the procedure is a Monte Carlo simulation and the use of a compact data structure called the zero-suppressed binary decision diagram, efficiently constructed through the frontier-based search. The novel measure is then computed for a diverse set of graphs, serving as benchmark for the proposed method. In closing, case studies on real-world networks are performed to ensure the consistency of the experimental with the actual

Sigma Coloring and Edge Deletions

A vertex coloring c : V(G) → N of a non-trivial graph G is called a sigma coloring if σ(u) is not equal to σ(v) for any pair of adjacent vertices u and v. Here, σ(x) denotes the sum of the colors assigned to vertices adjacent to x. The sigma chromatic number of G, denoted by σ(G), is defined as the fewest number of colors needed to construct a sigma coloring of G. In this paper, we consider the sigma chromatic number of graphs obtained by deleting one or more of its edges. In particular, we study the difference σ(G)−σ(G−e) in general as well as in restricted scenarios; here, G−e is the graph obtained by deleting an edge e from G. Furthermore, we study the sigma chromatic number of graphs obtained via multiple edge deletions in complete graphs by considering the complements of paths and cycles

The sigma chromatic number of the Sierpinski gasket graphs and the Hanoi graphs

A vertex coloring c : V(G) → of a non-trivial connected graph G is called a sigma coloring if σ(u) ≠ σ(v) for any pair of adjacent vertices u and v. Here, σ(x) denotes the sum of the colors assigned to vertices adjacent to x. The sigma chromatic number of G, denoted by σ(G), is defined as the fewest number of colors needed to construct a sigma coloring of G. In this paper, we determine the sigma chromatic numbers of the Sierpiński gasket graphs and the Hanoi graphs. Moreover, we prove the uniqueness of the sigma coloring for Sierpiński gasket graphs