Comparative study on discrete SI approaches to the graph coloring problem

The Graph Coloring Problem is an important benchmark problem for decision and discrete optimization problems. In this work, we perform a comparative experimental study of four algorithms based on Swarm Intelligence for the 3-Graph Coloring Problem: Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Cuckoo Search (CS) and FireFly Algorithm (FFA). For each algorithm, we test parameter settings published in the literature, as well as parameters found by an automated tuning methodology (irace). This comparison may shed some light at the strengths and weaknesses of each algorithm, as well as their dependence on parameter values.