Simulation

What is Simulation?

Simulation is a powerful tool used in the field of logistics to test the performance of a system under uncertain conditions. It involves creating a mathematical model that mimics the behavior of a real system and allows us to understand how it would perform in different scenarios.

In logistics, there are often many variables that can affect the performance of a system. These variables can include uncertain inputs, such as customer demand, or uncertain system configuration options, such as the number of resources available. By using simulation, we can account for these uncertainties and obtain probability distributions for the behavior of the system.

Let's consider an example to better understand the concept of simulation in logistics. Imagine a company that manufactures products and has a build plan process in place. The build plan process outlines the steps and resources required to produce the products. However, the company is unsure how the build plan will perform under different product demand scenarios.

To evaluate the performance of the build plan, the company can create a simulation model. This model would take into account the uncertain inputs, such as different levels of product demand, and the uncertain system configuration options, such as varying resource availability. By running the simulation model multiple times, the company can generate probability distributions for the outputs of the system, such as the number of products produced or the time taken to complete the build plan.

Simulation allows the company to gain insights into how the build plan would perform under different scenarios. It helps identify potential bottlenecks, inefficiencies, or areas of improvement. By analyzing the probability distributions obtained from the simulation, the company can make informed decisions and optimize its build plan process to meet customer demand effectively.

In summary, simulation is a mathematical technique used in logistics to test the performance of a system under uncertain conditions. It helps us understand how a system would behave in different scenarios by generating probability distributions for its outputs. By using simulation, companies can evaluate and optimize their processes, leading to improved efficiency and customer satisfaction.