Global optimization approaches such as Markov-chain Monte Carlo and GAs have been previously used to explore the vast configurational space of possible homotops for given particle shapes and compositions and find the lowest-energy chemical ordering. However, Monte Carlo simulations are often inefficient due to their inability to escape deep basins of the potential energy surface, whereas GAs not complemented with explicit relaxation steps decrease slowly within basins.