Optimization is a very important tool in business decisions, but there's a huge difference in outcomes if the business environment deviates from the assumptions used to optimize the strategy.
In this webinar we will demonstrate how to run optimization analyses under a context of uncertainty, using optimization in connection with Monte Carlo simulation, in order to find an decision strategy that is both optimized and robust in face of an uncertain future.
For example, how to optimize an investment strategy under uncertain project results (revenues, costs) and uncertain resource constraints (availability of resources, cost of resources).
We will show the difference between deterministic and stochastic optimization, and we can develop much more robust strategies by accounting for uncertainties in the models.