Generation of mass data for the simulation of a logistics network

The PTA supports the provision of actual data, which serves as reference data or reference distribution. By means of SQL scripts, the data is provided according to previously defined interfaces so that the subsequent process of generating artificial shipment data can generate consistent data. The process of generating the shipment data is implemented in Python. PTA advises the customer on the development of the architecture of the process and on performance-relevant aspects. The main challenge here is the generation of consistent mass data (several million data records) in a few hours by using clever caching techniques. Adequate methods from the field of statistics, such as sampling and imputation, are used to ensure that the key statistical indicators of the generated data correspond to the indicators of the reference distribution.