Evolutionary Algorithm Implementation for Good Graph Drawing(Graph Aesthetics)Using Fuzzy Fitness Function

Abstract

A graph is a collection of vertices or nodes, pairs of which are joined by lines or edges, can be used not only to represent physical relationships, but also to represent logical, biological, and arithmetic relationships. The attributes that define a good graph are called aesthetics. The problem of good graph drawing is the conflict of some aesthetics with one another. In this paper, Evolutionary Algorithm used with fuzzy fitness function to reduce the conflict and drawing Good Graph that it will convey the most meaning. Two types of crossover and two type of mutation are used, the chromosome represented as graph with N nodes, where N is the chromosome length ,and node is a gene in any chromosome . Good result can be obtained when Fuzzy set is used to compute fitness function .