Logistics Simulation

What is logistics simulation?

Logistics simulation is a method used to model, replicate, and analyze logistics processes and systems – usually in a digital environment. The goal is to understand, evaluate, and optimize these processes under different conditions. The systems involved can include warehouses, transportation chains, or production workflows.

There are several types of logistics simulation:

• Discrete simulation models individual events, such as loading a truck.

• Continuous simulation represents continuous flows like fluid movement.

• Agent-based simulation models each unit in the system (e.g., a forklift in a warehouse) as an independent agent with its own behavior.

• Hybrid simulation combines multiple approaches.

Typical applications of logistics simulation:

• Material flow

• Transport networks

• Shipping and returns logistics

• Production logistics

• Delivery and supply chain concepts

A practical example: logistics simulation can help determine whether the current number of loading bays at a distribution center is sufficient. Based on data like the number of incoming trucks per day, operating hours, and average unloading time, it can calculate potential waiting times and bay utilization. These insights support informed decisions, such as whether to build additional bays or implement a time-slot booking system.

Benefits of logistics simulation:

• Data-driven decision-making

• Testing of new logistics systems (e.g., a warehouse) before construction begins

• Exploration of “what-if” scenarios

• Identification and resolution of bottlenecks or overcapacity in existing systems