Model Overview – Customer Service at a Border Crossing

New releases of AnyLogic come with new example models. These help newcomers understand simulations and experienced users to learn about AnyLogic’s advanced capabilities. You can also find these models in AnyLogic Cloud.

New to AnyLogic is our Border Checkpoint model. It is based on the same principles as classical queueing systems, such as those found in banks, shops, and medical centers. The dynamics of these systems can be represented as a series of operations, a teller serving a customer for example. This allows business processes to be represented visually and means models can be flexible and scalable.

With the help of modeling, it is possible to experiment with facility layouts as well as assess the capacity and work rate.

In this post, we show how to model and analyze a variety of these business problems using the new border crossing model. You can also see the model at work in the AnyLogic Cloud.

Border crossing simulation model

The model is of a Russian-Finnish border checkpoint. Buses and cars arrive at the crossing; the people, cars, and buses are processed separately; and, no problems found, everyone continues their journey.

Vehicles begin queueing if they cannot immediately take a place at the entrance. This behavior is typical for agents, or entities, in models of customer service systems. Knowing the effect of arrival rate on queue length enables the optimization of staffing and scheduling.

Checkpoint entrance

In queueing models, different types of input streams can be separated to allow the application of different characteristics and logic. With our model, the flows divide into cars and buses to allow different processing.

Incorporating personnel allows the workload, scheduling, and level of service to be analyzed. In this model, it is possible to vary the number of inspectors checking vehicles and passengers. Changes can be tested, and the effects assessed. Visualization also means bottlenecks and problem areas can be identified quickly.

Vehicle inspection simulation

Unlike analytical models, simulation models consider random variables and show dynamic behavior. In our model, the arrival rate of vehicles and the number of passengers are randomly varied using a statistical distribution.

Simulation modeling goes beyond just testing the behavior rules of a system. The whole performance of the facility can be tested by capturing the nature and dynamics of how people and vehicles move through it. The border checkpoint model allows you to test both the configuration of the roads and the checkpoint building.

With an interest in extremes, it is also possible to estimate the capacity of the system and its stability at peak loads. The system can be stress-tested by altering the input values until the model is overloaded. For example, we can explore the limits of vehicle arrival rates in the border crossing model.

Model statistics

Under certain circumstances it is possible to use optimization. Business challenges which need to improve specific parameters and that have defined constraints can be resolved with the help of simulation modeling and optimization. The optimization software adjusts model input parameters to find parameter configurations that best fit the requirements. In our border crossing example, this could enable the balancing of staffing and scheduling to demand.

This concludes our look at the model from the business side. Simulation modeling is a powerful tool for solving customer service business challenges. With detailed dynamic models and simulation, it is possible to conduct analysis, test ideas, and develop solutions.

We will continue this blog with a look at the technical features of the border crossing model – Investigating the libraries used, learning tips and tricks, and getting advice from the model developer. Don’t miss it! Connect with us on LinkedIn, Facebook, Google+ and Twitter!