A novel improved slime mould algorithm for engineering design

Metaheuristic intelligent optimization algorithm is an effective method to settle high-dimensional nonlinear complicated optimization problems. Slime mould algorithm is a novel intelligent optimization algorithm proposed in 2020. However, the basic slime mould algorithm still has shortcomings, such as slow convergence rate, easy falling into local extremum, and imbalanced exploration and exploitation capabilities. To further enhance the optimization capability and expand the application scope of the slime mould algorithm, a slime mould algorithm based on the mechanism of multi-strategy information interaction and optimally oriented initialization (MSII-SMA) is proposed. Three improved mechanisms are introduced into the algorithm and the time complexity of MSII-SMA is analyzed. To verify the optimization effect, MSII-SMA and the other 5 typical comparison algorithms are applied to settle the CEC2015 test function set. The analysis of the optimization accuracy, convergence curve, Friedman test, boxplot and scalability test shows that the optimization ability, convergence rate, stability and scalability of MSII-SMA are evidently better than the comparison algorithm. Finally, MSII-SMA and other comparison algorithms are used to settle engineering design optimization problems with different complexity. The experimental results verify the universality, reliability and preponderance of MSII-SMA in dealing with engineering design constraint optimization problems.