Global optimisation;Slime mould algorithm;Swarm-intelligence;Experiment;Real-world problems

In this paper, the performance of the slime mould algorithms (SMA) is studied. The original SMA algorithm is enhanced by several mechanisms to achieve better results in various problems. The Eigen transformation, linear reduction of population size, and perturbation of the solution are proposed and combined together with various settings of control parameters. All 16 newly proposed variants of SMA are compared with the original SMA and 16 various nature-inspired methods. All the algorithms are applied to 22 real-world problems called CEC 2011. Achieved results illustrate the good performance of the newly proposed SMA variants, especially compared with the original SMA algorithm.