Abstract: A system and method are disclosed for a warehouse management system having a task database and a server comprising a processor and memory. The system groups one or more tasks from the task database into one or more groups, estimate the latest feasible start time for each group of the one or more groups and assigns a priority for the one or more tasks in each group based, at least in part, on the estimated latest feasible start time for each group.

Abstract: A system and method are disclosed for displaying a visualization of tasks to be performed across one or more time intervals. Embodiments include receiving two or more tasks from a task database comprising one or more attributes in a table format, the table having two or more rows and two or more columns, adding a column to each of the two or more tasks comprising the volume of tasks to be cumulatively performed during a time interval and adding a column to each of the two or more tasks comprising the cumulative volume due during the time interval. Embodiments also include displaying, on a graphical user interface, a visualization of the cumulative volume due and the cumulative planned curve representing the volume of tasks to be performed across one or more time intervals.

Abstract: A system and method are disclosed including a demand planner that receives a demand for two or more options that are needed to produce at least one automobile. The demand planner also models the two or more options as a network of arcs and nodes and generates one or more valid configurations of the two or more options. The demand planner further determines the demand for the one or more valid configurations and causes at least one manufacturer to manufacture, the at least one automobile based on the determined demand for the one or more valid configurations.

Abstract: A system and method are disclosed including a demand planner that receives a demand for two or more options that are needed to produce at least one automobile. The demand planner also models the two or more options as a network of arcs and nodes and generates one or more valid configurations of the two or more options. The demand planner further determines the demand for the one or more valid configurations and causes at least one manufacturer to manufacture, the at least one automobile based on the determined demand for the one or more valid configurations.

Abstract: A system and method are disclosed including a production planner that receives a sales forecast for configurations of an automobile. The demand planner also receives constraints associated with an automobile supply chain. The demand planner further models configurations and constraints as a mixed integer linear programming problem, determines a production plan for automobiles, and sends instructions to cause automated machinery to retrieve an amount of automobiles equal to a forecasted production level minus a current inventory level and to move the amount of the automobile to an inventory location of the automobile.

Abstract: A system and method are disclosed including a production planner that receives a sales forecast for configurations of an automobile. The demand planner also receives constraints associated with an automobile supply chain. The demand planner further models configurations and constraints as a mixed integer linear programming problem, determines a production plan for automobiles, and sends instructions to cause automated machinery to retrieve an amount of automobiles equal to a forecasted production level minus a current inventory level and to move the amount of the automobile to an inventory location of the automobile.

Abstract: A system and method are disclosed including a production planner that receives a sales forecast for configurations of an automobile. The demand planner also receives constraints associated with an automobile supply chain. The demand planner further models configurations and constraints as a mixed integer linear programming problem, determines a production plan for automobiles, and sends instructions to cause automated machinery to retrieve an amount of automobiles equal to a forecasted production level minus a current inventory level and to move the amount of the automobile to an inventory location of the automobile.