The optimizing-simulator: merging simulation and optimization using approximate dynamic programming

There has long been a competition between simulation and optimization in the modeling of problems in transportation and logistics, machine scheduling and similar high dimensional problems in operations research. Simulation strives to model operations, often using rule-based logic. Optimization strives to find the best possible solution, minimizing costs or maximizing profits. In this tutorial, we show how these two modeling technologies can be brought together, combining the flexibility of simulation with the intelligence of optimization.