Many real-world optimization problems have the characteristics of being nonlinear, multimodal, high-dimensional, dynamic, multiobjective, and so on, which are very complex to be solved. In recent years natural-inspired algorithms, which are a set of novel problem-solving methodologies and approaches, have been attracting considerable attention for their good performance. Artificial neural networks (ANN), fuzzy systems (FS), evolutionary computing (EC), and swarm intelligence (SI), which have drawn inspiration from different natural phenomena or systems, are the typical natural-inspired algorithms and have been applied successfully to solve real-world problems. Despite the popularity of natural-inspired algorithms, there are still many challenging issues that require further research efforts.

We invite authors to contribute original research articles that propose novel real-world problems solved by natural-inspired algorithms. We are also interested in articles that explore the theoretical analysis for natural-inspired algorithms by various mathematical approaches and the modifications for natural-inspired algorithms in order to improve the performance.