The history of Evolutionary Computation has progressed from formal studies to a method-centric and framework-centric period, where many algorithms are described as methods or frameworks and their development is primarily performance-driven. We are still in a phase of optimization research where many researchers are developing “new” optimization algorithms, while not truly understanding them. With this special issue we are trying to show the importance of the move from a performance-driven community to a community in which scientific understanding is more important, in which the design of new algorithms (heuristics) becomes a science instead of an art (the future). …
