Gradation in Greyscales of Graphs
In this work we present the notion of greyscale of a graph as a colouring of its vertices that uses colours from the real interval [0,1]. Any greyscale induces another colouring by assigning to each edge the non-negative dif- ference between the colours of its vertices. These edge colours are ordere...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/125728 |
| Acceso en línea: | https://hdl.handle.net/11441/125728 |
| Access Level: | acceso abierto |
| Palabra clave: | Graph colouring Greyscale Minimum gradation Graph algorithms |
| Sumario: | In this work we present the notion of greyscale of a graph as a colouring of its vertices that uses colours from the real interval [0,1]. Any greyscale induces another colouring by assigning to each edge the non-negative dif- ference between the colours of its vertices. These edge colours are ordered in lexicographical decreasing ordering and give rise to a new element of the graph: the gradation vector. We introduce the notion of minimum grada- tion vector as a new invariant for the graph and give polynomial algorithms to obtain it. These algorithms also output all greyscales that produce the minimum gradation vector. This way we tackle and solve a novel vectorial optimization problem in graphs that may produce more satisfactory solu- tions than those ones generated by known scalar optimization approaches. The interest of these new concepts lies in their possible applications for solving problems of engineering, physics and applied mathematics which are modeled according to a network whose nodes have assigned numerical values of a certain parameter delimited by a range of real numbers. The ob- jective is to minimize the differences between each node and its neighbors, ensuring that the extreme values of the interval are assigned. |
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