Simulating a Theme Park: Understanding queue times with R

Long lines are always off-putting, especially when you are waiting to soar through space or sail along the Great Barrier Reef. As the summer holidays continue, I’m sure nearly everyone will be queueing for something, and hopefully, you’re lucky enough to be heading straight for the Magic Kingdom. Maybe you’re in one of those queues while you read this blog! Some code is included to support the examples, but the full code can be found on my GitHub, which is linked at the end of the article. The project uses R and the simmer package for Discrete Event Simulation. Please enjoy! <h2>Concept Review — Discrete Event Simulation</h2> So what will it take to simulate a theme park on my laptop? And will it look anything like Game Central Station from Wreck-it-Ralph? I’m afraid not … the code written in R will use Discrete Event Simulation or DES, which really just shows what could happen in a process over time. The major use case of DES is to optimize processes which is why it is commonly used in operations research. Simulations allow decision-makers to view a typical process after many iterations and see how it could be improved. For example, would adding extra machines to a factory line reduce bottlenecks in producing a product? <a href="https://towardsdatascience.com/simulating-a-theme-park-understanding-queue-times-with-r-100b12d97cd3">Read More</a>