  Experimental studies are prevalent in Evolutionary Computation (EC), and
concerns about the reproducibility and replicability of such studies have
increased in recent times, reflecting similar concerns in other scientific
fields. In this article, we discuss, within the context of EC, the different
types of reproducibility and suggest a classification that refines the badge
system of the Association of Computing Machinery (ACM) adopted by ACM
Transactions on Evolutionary Learning and Optimization
(https://dlnext.acm.org/journal/telo). We identify cultural and technical
obstacles to reproducibility in the EC field. Finally, we provide guidelines
and suggest tools that may help to overcome some of these reproducibility
obstacles.
