Solving Graph Coloring Problem Using New Greedy and Probabilistic Method

Nowadays, graph coloring as a combinatorial optimization is used in different engineering domains. The chromatic integer of a connected graph is computed using either deterministic or stochastic methods. This research implements a new probabilistic approach to find the minimal coloring based on the largest degree of a graph. This stochastic method is developed using the greedy design strategy and is tested on different benchmark graph instances. It has been found that the proposed stochastic hybrid design strategy converges to the solution with reduced complexity. The performance measurement of the proposed approach is expected since it provides better performance than the recent well-known techniques.