Swarm algorithm, Harris hawks optimisation, real-worldproblems, archive, experimental comparison.

This paper proposes an enhanced variant of the novel and popular Harris Hawks Optimisation (HHO) method. The original HHO algorithm was studied in many research projects, and a lot of hybrid (cooperative) variants of HHO was proposed. In this research study, an advanced HHO algorithm with an archive of the old solutions is proposed (HHOA). The proposed method is experimentally compared with the original HHO algorithm on a set of 22 real-world problems (CEC 2011). The results illustrate the superiority of HHOA because it outperforms HHO significantly in 20 out of 22 problems, and it is never significantly worse. Four well-known nature-based algorithms were employed to compare the efficiency of the proposed algorithm. HHOA achieves the best results in overall statistical comparison. A more detailed comparison shows that HHOA achieves the best results in half real-world problems, and it is never the worst-performing method. A newly employed archive of old solutions significantly increases the performance of the original HHO algorithm.