A Memetic Algorithm with Adaptive Operator Selection for Graph Coloring

Abstract

We present a memetic algorithm with adaptive operator selection for k-coloring and weighted vertex coloring. Our method uses online selection to adaptively determine the couple of crossover and local search operators to apply during the search to improve the efficiency of the algorithm. This leads to better results than without the operator selection and allows us to find a new coloring with 404 colors for C2000.9, one of the largest and densest instances of the classical DIMACS coloring benchmarks. The proposed method also finds three new best solutions for the weighted vertex coloring problem. We investigate the impacts of the different algorithmic variants on both problems.