Greedy coloring
In the study of graph coloring problems in mathematics and computer science, a greedy coloring is a coloring of the vertices of a graph formed by a greedy algorithm that considers the vertices of the graph in sequence and assigns each vertex its first available color. Greedy colorings do not in general use the minimum number of colors possible. However, they have been used in mathematics as a technique for proving other results about colorings and in computer science as a heuristic to find colorings with few colors.
A crown graph (a complete bipartite graph Kn,n, with the edges of a perfect matching removed) is a particularly bad case for greedy coloring: if the vertex ordering places two vertices consecutively whenever they belong to one of the pairs of the removed matching, then a greedy coloring will use n colors, while the optimal number of colors for this graph is two. There also exist graphs such that with high probability a randomly chosen vertex ordering leads to a number of colors much larger than the minimum. Therefore, it is of some importance in greedy coloring to choose the vertex ordering carefully. The number of colors produced by the greedy coloring for the worst ordering of a given graph is called its Grundy number.
It is NP-complete to determine, for a given graph G and number k, whether there exists an ordering of the vertices of G that forces the greedy algorithm to use k or more colors. In particular, this means that it is difficult to find the worst ordering for G.
The vertices of any graph may always be ordered in such a way that the greedy algorithm produces an optimal coloring. For, given any optimal coloring in which the smallest color set is maximal, the second color set is maximal with respect to the first color set, etc., one may order the vertices by their colors. Then when one uses a greedy algorithm with this order, the resulting coloring is automatically optimal. More strongly, perfectly orderable graphs (which include chordal graphs, comparability graphs, and distance-hereditary graphs) have an ordering that is optimal both for the graph itself and for all of its induced subgraphs. However, finding an optimal ordering for an arbitrary graph is NP-hard (because it could be used to solve the NP-complete graph coloring problem), and recognizing perfectly orderable graphs is also NP-complete. For this reason, heuristics have been used that attempt to reduce the number of colors while not guaranteeing an optimal number of colors.
...
Wikipedia