“…The optimization of real-world problems is characterized by large scale, many constraints and variables, which makes it difficult for traditional algorithms to find the solution in a short time. In order to improve the calculation accuracy and speed, intelligent optimization algorithms (such as simulated annealing algorithm [1,2] , neural network algorithm [3,4] , homotopy algorithm [5,6] , genetic algorithm [7,8] , ant colony algorithm [9,10] , multiscale algorithm [11][12][13] and particle swarm algorithm [14,15] , etc.) have been proposed and applied in various fields.…”