Abstract. Solving a problem once may not be enough. Many real-world optimization problems require continuous monitoring and re-optimization. In this talk, we use a dynamic stacking and scheduling scenario to illustrate the importance and challenges of dynamic optimization including uncertainty, open-endedness, asynchronicity and information delays. We showcase the problem definitions, simulation and supporting software architecture for solving these types of problems and present some analysis and visualization techniques that can help to understand the progression of problem states.