The Route Optimizer application uses linear optimization (in Julia) and Google Maps to create the shortest route for various adventures. Most solutions to the traveling salesman problem focus on minimizing distances but, by using real-time traffic data available as an API service, this application optimizes routes based on duration instead. Read more about how we made it.

The Investment Portfolio application uses a Monte Carlo method (in Python) to simulate market positions based on historical data. Adjust your portfolio to achieve a higher average return while minimizing your chance of losing money. Then, see where your results rank on the leaderboard.

This innovative tool helps states and regulators make decisions on electricity supply and demand to reduce the vulnerability to drought by reducing water needs. The simulation allows users to change energy demand assumptions, determine how electricity is supplied, and see how those decisions impact the power supply and demand balance, water use, air pollution, carbon dioxide emissions and costs.

The Nurse Scheduler tackles the weekly scheduling challenges of a typical enterprise. In this case, the workers are nurses with different skill sets across Oncology, Cardiac Care, and Emergency Room services. The nurses have various pay rates and ever-changing compatibility preferences. For a given a set of workers and a desired schedule, the application optimizes all the shifts for the week. It balances costs, fairness, and worker hours based on how you wish to weight the constraints.

The Population Health Simulator tests the impact of health policy and investment decisions over time. Your goal is to reduce the number of people at risk for disease while cutting costs, by selecting from different options for patient engagement and provider productivity. Then, compare your scenario to a global leaderboard.

* This simulation currently only works in Firefox & Chrome