Data processing: generic control systems or specific application – Specific application – apparatus or process – Product assembly or manufacturing
Reexamination Certificate
1998-09-16
2001-05-15
Millin, Vincent (Department: 2165)
Data processing: generic control systems or specific application
Specific application, apparatus or process
Product assembly or manufacturing
C700S096000, C700S097000, C700S099000, C700S103000, C706S013000
Reexamination Certificate
active
06233493
ABSTRACT:
TECHNICAL FIELD OF THE INVENTION
This invention relates to computer implemented management for business enterprises, and more particularly to a system and method for planning a portfolio of products to be developed.
BACKGROUND OF THE INVENTION
Computer implemented planning and scheduling systems are increasingly being used in factories and other enterprises. Such systems model the enterprise environment and provide schedules for producing items to fulfill consumer demand within the constraints of the environment.
Typically, planning and scheduling problems can be represented as a constrained optimization problem. For example, consider the problem of sequencing a set of tasks on a single resource in a manufacturing environment. Assume each task has a deadline and that the objective is to schedule each task so that it is completed by its deadline. One way to view this problem is as a search in a space of start times. Under this view, the problem is a constrained optimization problem in which the variables are the start times, the constraint is that no tasks can overlap, and the objective is not missing deadlines.
One enterprise activity whose scheduling and planning problems have not been adequately addressed by computer-implemented methods is new product development. Companies rely on new product development to achieve strategic positioning or increase revenue growth. This places an emphasis on optimizing the enterprise's product portfolio, that is, the selection of what products to make and the associated resource scheduling.
Many existing techniques and tools that have been developed for other types of enterprise management can be applied to portfolio planning. For example, a supply chain management system is available from i2 Technologies, Inc. of Irving, Tex. Many of the modeling structures and processes used for supply chain management can be applied to product development management. However, unique problems that arise in portfolio planning give rise to a need for a model especially formulated for product development.
SUMMARY OF THE INVENTION
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.
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Cherneff Jonathan M.
Kumar Krishna
Baker & Botts L.L.P.
i2 Technologies, Inc.
Millin Vincent
Nguyen Cuong H.
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