Optimization on complex systems

This special issue aims to collect the new emerging works in the field of complex systems, particularly in regards to the development of new analytical models and novel applications, as well as on the design of new nature-inspired optimization algorithms. Many problems in all the traditional research areas are often hard to solve, mainly due to the difficulty in understanding their indirect causes and effects, which are not related in an obvious way. Studying how a system interacts with the environment, or how simple components give rise to the global collective behaviour of the system, or even how parts of a system interact with each other, is nowadays one of the most challenging and interesting research areas in every discipline because of its utmost relevance. Because the parameters that influence the structures and dynamics over time are unknown and often impossible to be analytically solved, to find the solutions of such problems becomes a not trivial job. Nature-inspired algorithms, or simply Evolutionary Algorithms, seem to be more suitable on these kinds of tasks than the standard methods, mainly when the solutions are nonlinear or not known a priori. Thus, developing mathematical models becomes useful for having a better understanding of the behaviour of dynamic processes (e.g. the dynamic processes of biochemical networks), and for predicting their behaviours under certain conditions. In the computational biology area, for example, it has