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Another interesting use of agent-based modeling: Theme parks

This paragraph describes the construction and uses of an agent-based model of an amusement park, used to maximize the uses of all rides in the park.

Another application of ABM to flow management is the simulation of customer behavior in a theme park or supermarket. The collective patterns generated by thousands of customers can be extremely complex as customers interact: for example, how long one waits at an attraction in a theme park depends on other people's choices. A major theme park resort company was thinking about how to improve adaptability in labor scheduling, but knew that this depended on knowing more about the optimal balance of capacity and demand. Axtell and Epstein developed ResortScape (13), an agent-based model of the park that provides an integrated picture of the environment and all of the interacting elements that come into play in such a resort. The model provides a fast in silico way for managers to identify, adjust, and watch the impact of any number of management levers such as:

  • When or whether to turn off a particular ride.
  • How to distribute rides per capita throughout the park space.
  • What is the tolerance level for wait times.
  • When to extend operating hours.

In the simulation, agents represent a realistic and changeable mix of both supply (attractions, shops, food concessions) and demand (visitors with different preferences) elements of a day at the park. Leveraging existing resources and data, such as customer surveys, segmentation studies, queue timers, people counters, attendance estimates, and capacity figures, the model generates information about guest flow. Users can design and run an infinite number of scenarios to study the dynamics of the park space, test the effectiveness of various management decisions, and track visitor satisfaction throughout the day.

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