Rajasekhar Mallipeddi

7266549, Sep 4, 2007

Sep 14, 2004

10/940851

Pedro S. de Souza - Flower Mound TX, US
Assia Abada - Irving TX, US
Rajasekhar Mallipeddi - Flower Mound TX, US
Yasser A. Kazzaz - Irving TX, US

i2 Technologies US, Inc. - Dallas TX

G06F 17/30

707 3, 707 2, 707 10, 707100

In one embodiment, a method for optimization using multi-dimensional data includes receiving a problem instance to be solved using an optimization engine. The problem instance is specified in a multi-dimensional format associated with a multi-dimensional data model that includes multiple data dimensions each including a hierarchy of members. The problem instance includes an objective function, an optimization operator, and one or more constraints. The optimization engine is unable to solve the problem instance including the objective function, the optimization operator, and the one or more constraints in the multi-dimensional format. The method also includes, using a transformation module, transforming the problem instance including the objective function, the optimization operator, and the one or more constraints into a format appropriate for the optimization engine and communicating the transformed problem instance including the objective function, the optimization operator, and the one or more constraints to the optimization engine to be solved.

7734617, Jun 8, 2010

Jun 8, 2007

11/760229

Pedro S. de Souza - Flower Mound TX, US
Assia Abada - Irving TX, US
Rajasekhar Mallipeddi - Flower Mound TX, US
Yasser A. Kazzaz - Irving TX, US

i2 Technologies US, Inc. - Dallas TX

G06F 7/00
G06F 17/30

707713, 707602, 707756, 707957

In one embodiment, a method for optimization using multi-dimensional data includes receiving a problem instance to be solved using an optimization engine. The problem instance is specified in a multi-dimensional format associated with a multidimensional data model that includes multiple data dimensions each including a hierarchy of members. The problem instance includes an objective function, an optimization operator, and one or more constraints. The optimization engine is unable to solve the problem instance including the objective function, the optimization operator, and the one or more constraints in the multi-dimensional format. The method also includes, using a transformation module, transforming the problem instance including the objective function, the optimization operator, and the one or more constraints into a format appropriate for the optimization engine and communicating the transformed problem instance including the objective function, the optimization operator, and the one or more constraints to the optimization engine to be solved.

7031955, Apr 18, 2006

Apr 27, 2001

09/844847

Pedro S. de Souza - Flower Mound TX, US
Assia Abada - Irving TX, US
Rajasekhar Mallipeddi - Flower Mound TX, US
Yasser A. Kazzaz - Irving TX, US

i2 Technologies US, Inc. - Dallas TX

G06F 17/30

707 3, 707 10, 707100, 707 2

A system () for optimization using multi-dimensional data includes a server () that uses a multi-dimensional data model to organize data stored at one or more data storage locations (). The multi-dimensional data model includes a number of data dimensions () that each include a hierarchy of members (). The server () receives input from a user specifying a problem instance to be solved using an optimization engine (). The problem instance is specified by the user in a multi-dimensional format and the optimization engine () is unable to solve the problem instance in the multi-dimensional format. The system () also includes a transformation module () that receives the problem instance in the multi-dimensional format, transforms the problem instance into a format appropriate for the optimization engine (), and communicates the transformed problem instance to the optimization engine () to be solved.