Computer-implemented product development planning method

DETAILED DESCRIPTION One aspect of the invention is a system for providing data representing an "optimal" product portfolio, for use in enterprise product development management.
The system has an optimizing engine that uses both a genetic algorithm and a constraint engine.
The optimizing engine operates on an enterprise model having the following components: product models representing products proposed to be manufactured by said enterprise, component models representing components from which products are made, task models representing tasks to be performed in the development of a component, and resource models representing resources available for use in performing tasks.
The genetic algorithm is used to provide sequences of products as candidates for the portfolio.
The constraint engine builds a schedules for each sequence, subject to constraints of the model.
The genetic algorithm and constraint engine cooperate in an iterative process to evaluate each sequence in terms of constraint violations of constraints associated with the model, and to provide better sequences.
The result of this process is a "best" portfolio, that is, one that best satisfies constraints, as well as data representing a pipeline for developing the portfolio.
Constraint violations can be translated to an objective criteria, such as profit such that the optimization is in terms of profit maximization.
An advantage of the invention is that optimizes a product portfolio subject to the constraint of the product pipeline.
The system rapidly converges to a good solution but is also able to quickly propagate incremental changes to the schedule.