Sas Institute Inc.

Jie Zhong

Rajendra Singh Solanki

Yinhua Wang

Michael James Leonard

Li Xu

Rajib Nath

Kyungduck Cha

Macklin Carter Frazier

Hao Cheng

Elaine Kearney Kowalewski

A computer monitors a state of a system. A time branch is defined for each valid value of each discrete variable. A system model is executed with observed values to update each time branch and determine a probability associated with each time branch. A discrete variable is selected, and a sequence duration value is incremented. When the incremented sequence duration value is greater than a predefined minimum sequence duration value, a probability change value is computed for the discrete variable, and, when the computed probability change value is less than or equal to a synchronization probability change value, a continuous value for each continuous variable for each time branch of the discrete variable is synchronized, and the sequence duration value for the selected discrete variable is reinitialized. The continuous value for at least one non-observed continuous variable is output.

State monitoring system

Time-series projections can be analyzed and manipulated via an interactive graphical user interface generated by a system. The graphical user interface can include a graph depicting an aggregated time-series projection (ATSP) over a future time. The ATSP can be generated by aggregating multiple time-series. The system can receive user input indicating that an existing value in the ATSP is to be overridden with an override value. In response, the system can adjust the ATSP using the override value to generate an updated version of the ATSP. The system can display the updated version of the ATSP in the graphical user interface. The system can also propagate the impact of overriding the existing value with the override value through the multiple time-series. The system can display an impact analysis portion within the graphical user interface indicating the impact of overriding the existing value with the override value on the multiple time-series.

Interactive graphical user-interface for analyzing and manipulating time-series projections

Computer-implemented systems and methods for determining promotion prices for a plurality of items. A system and method can be configured to receive electronic data about items for a promotion event and to receive electronic data about vehicles for a promotion event. An optimizer, which is implemented on a data processor, includes or has access to an optimization formulation for determining optimal promotion prices for the items and for determining assignments of the vehicles to the items for promoting the items during the promotion event.

Computer-implemented promotion optimization methods and systems

Computer-implemented systems and methods for regular pricing optimization. A system can include decomposing a pricing situation into sub-problems. A non-linear optimization problem is solved to determine continuous optimal prices. A mixed integer linear programming problem is solved to snap prices to grid points.

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Jie Zhong