Enterprise planning is the "planning" part of the sales and operations planning business process. Atlantic Planner is used to determine the optimal way of meeting a company's demand forecast. Using linear and mixed-integer programming, Atlantic determines the best way to meet demand considering production costs, production capacity, distribution costs, inventory capacity, and inventory targets. The resulting plan describes which plants and distributions centers to source demand from given all the costs and constraints.
Atlantic Planner makes scenarios analysis easier by enabling evaluation of multiple demand plans, user fixed sourcing and other manipulation of constraints.
Atlantic Planner can also be used to add linear and mixed integer programming optimization to plant scheduling models. This capability allows advanced schedulers to optimize shift manpower, flex inventory targets and optimize machine assignment prior to doing detailed scheduling. For certain classes of problems, this advanced capability eases the creation of feasible schedules and adds additional cost optimization capabilities to Atlantic Scheduler.
Flexible Model Formulation
Atlantic Planner is Math Programming based. It has a data-driven matrix generator that can create literally any math programming model involving Linear Programming, Mixed-Integer Programming, or Mixed-Integer Quadratic Programming. We provide links to commercial solvers like Gurobi and Xpress as well as the open source solvers. The solutions from the solvers are placed back in the catalog where they can be analyzed with a powerful reporting tool.
In order to create a model with the matrix generator we start with the Matrix cube (table) which is defined on dimensions MatrixRows and MatrixColumns. The entries in MatrixRows are classes of rows or constraints in the model, e.g., material balance rows by time period, or capacities by time period. The entries in MatrixColumns are classes of variables in the model, e.g., manufacturing operations by facility by time period, product inventory carryovers by time period, available capacities by facility by time period, etc. As shown in the screen below, MatrixRows lead to policies for row sense and right hand side values, MatrixColumns lead to policies for variable bounds and costs. The user/modeler can populate the Matrix formulation with catalog data by drag-and-drop. What could be easier?
All data is held in memory, made accessible through a Data Catalog which you will find to be amazingly familiar and easy to use.
Example Generic Planning Matrix