In a globally connected society, international meetings are becoming increasingly common, but this takes away little of the burden in planning or attending them. Thus, when planning an international scientific or business meeting, it is exceedingly important to choose a meeting location such that attendees will be able to contribute at peak productivity. We present an algorithm to determine the best meeting location for any given group of attendees by modeling the problem as a network of interconnected optimization problems, and we developed an advanced Java program that utilizes hundreds of thousands of custom­-crafted data entries and calls to the Google API to model the impact of jet lag and climate shock on attendees.