Abstract: Computer-readable media, methods, and systems are disclosed for electronically creating an improved timeline of events for product-location pairs. A machine learning model is trained on historical data to generate a demand forecast. Input requirements including an initial timeline of events for product-location pairs are received. Using combinatorial branch-and-bound along with the trained machine learning model, the improved timeline of events for product-location pairs is generated.

Abstract: Various embodiments of systems and methods for integrating a calculation engine of an in-memory database with a software component are described herein. A control unit schedules and triggers jobs to be processed by an operational unit. The control unit and the operational unit are at an application level. The operational unit divides a job workload corresponding to a job trigger into work packages based on one or more parameters. The work packages are sent to a calculation engine in an in-memory database. At the in-memory database, operations are performed on the work packages and an output is generated. A log in the control unit is updated based on the output.

Abstract: Various embodiments of systems and methods for integrating a calculation engine of an in-memory database with a software component are described herein. A control unit schedules and triggers jobs to be processed by an operational unit. The control unit and the operational unit are at an application level. The operational unit divides a job workload corresponding to a job trigger into work packages based on one or more parameters. The work packages are sent to a calculation engine in an in-memory database. At the in-memory database, operations are performed on the work packages and an output is generated. A log in the control unit is updated based on the output.