An aggregate plan is a statement of future resources and finished goods inventory levels that must be made available to enable a manufacturing organization to meet its forecast sales demand. The aggregate planning process must enable the strategic business objectives of a manufacturing organization to be quickly converted into short-term operational plans that are economical to implement. This link between strategy and the day-to-day activities of an organization is becoming increasingly important in enabling organizations to cope with the faster rate at which business objectives must be changed in order to remain competitive.
This paper initially examines the aggregate planning process and describes the basic tasks involved. Current methods of setting aggregate plans are then compared and the main limitations of such techniques highlighted. Using an aggregate planning example, the paper then explains how genetic algorithms can be used to develop such plans and illustrates how this type of algorithm provides the means by which the limitations of existing aggregate planning techniques can be overcome.
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