  The ultimate goal of all optimization methods is to solve real-world
problems. For a successful project execution, knowledge about optimization and
the application has to be pooled. As it is too inefficient to highly train one
person in both fields, a team of experts is usually put together.
Unfortunately, communication errors must be expected when several people
collaborate. In this work, we deal with the avoidance and the repair of these
communication errors. The tools proposed in this regard are, among others, the
algorithm engineering cycle, checklists for structuring communication, and
knowledge databases. The discussion is enriched with examples from continuous
optimization, but most tools have a much wider applicability, even beyond
optimization.
