摘要：Genetic and evolutionary algorithms have achieved impressive success in solving various optimization problems. In this work, an improved genetic-evolutionary algorithm (IGEA) for the grey pattern problem (GPP) isdiscussed. The main improvements are due to the specific recombination operator and the modified tabu search (intraevolutionary) procedure as a post-recombination algorithm, which is based on the intensification and diversification methodology. The effectiveness of IGEA is corroborated by the fact that all the GPP instances tested are solved topseudo-optimality at very small computational effort. The graphical illustrations of the grey patterns are presented.
关键词：combinatorial optimization; heuristics; genetic-evolutionary algorithms; grey pattern problem
