Algorithm 1 Brain Storm Optimization (BSO)

1:Initialization: Randomly generate $\lambda$ individuals (potential solutions) to form the initial population $P=\{{\xi }_1,{\xi }_2,\dots ,{\xi }_{\lambda }\}$ and evaluate the $\lambda$ individuals; 2:while fail to achieve the predetermined maximum number of iterations do 3:   Clustering: Use clustering algorithms to divide $\lambda$ individuals into m clusters; 4:   Disrupting: The mutation occurs with a certain probability, and a randomly selected cluster’s central individual is replaced by a randomly generated new individual; 5:   Updating: Randomly choose one or two clusters to create a new individual;    Compare the newly generated individual and the original individual with the same individual index. The better one will be saved as the new individual;    Update the whole population; the offspring population is recorded as $P^{\prime }=\{{\xi }_1^{\prime },{\xi }_2^{\prime },\dots ,{\xi }_{\lambda }^{\prime }\}$. Evaluate the individuals in $P^{\prime }$; 6:end while 7:Output the most optimal solution discovered.