Jda Software Group, Inc.

O9 Solutions, Inc.

Blue Yonder Group, Inc.

Narasimha Kamath

Tushar Shekhar

Koustuv Chatterjee

S Pandiarajan

Dinesh Damodaran

Mayuri Deb

Prashant Jhaba

Deba Kalyan Mohanty

Devender Chauhan

Kshitiz Uttam

Rohit Jangid

Systems and techniques for dynamic memoryless demand-supply pegging are described herein. An identification may be received of a demand to be pegged. An inventory may be determined for a material node at a time bucket. A set of other demands may be identified for the material node at the time bucket. A quantity to be pegged may be calculated. A quantity to skip may be calculated based on a sum of demand units corresponding to members of the set of other demands having a lower priority than the demand. A supply set of units may be identified. A pegged subset of the supply set of units may be generated by skipping members of the supply units equal to the quantity to skip. A graphical representation of the supply set of units for the time bucket may be output including identification of members of the pegged subset.

Dynamic memoryless demand-supply pegging

Systems and techniques for aggregated physical and logical network mesh view are described herein. A selection may be obtained of a portion of a graph network data structure. Nodes may be identified in the portion of the graph network data structure. Geolocation data may be determined for each node of the nodes. Geographical boundaries may be calculated for the portion of the graph network data structure. A geographical map and a network map may be generated. A physical network view may be generated for display in the user interface as an aggregated view of the geographical map and the network map. The geographical map may represent a physical layer and the network map may represent a logical layer. The aggregated view may be output for display with a set of controls that correspond to the physical layer and a set of controls that correspond to the logical layer.

Aggregated physical and logical network mesh view

A system and method are disclosed including a supply chain network including one or more entities, one or more items and a plan explainer. The plan explainer generates an optimum inventory level based on a root cause of a goal violation by modeling the supply chain network and one or more business objectives as a hierarchy of objective functions. The plan explainer also solves the hierarchy of objective functions, stores plan explanation data and retrieves the plan explanation data. The plan explainer further generates the root cause of the goal violation by parsing the retrieved plan explanation data and calculates the optimum inventory level based on the root cause of the goal violation. In response to the calculated optimum inventory level, at least one of the one or more entities adjusts inventory levels of the one or more items according to the optimum inventory level. Other embodiments are also disclosed.

System and method of root cause analysis of objective violations

Systems and techniques for read-write network visualization are described herein. A selected sub-region of a visual representation of a graph network may be displayed based on inputs received from a user. Boundaries for the selected sub-region of the visual representation of the graph network may be calculated. State data may be captured for a portion of the graph network associated with the selected sub-region using the calculated boundaries for the selected sub-region of the visual representation upon activation of an edit mode user interface control. A change to an element of the graph network may be identified. The graph network may be modified based on the change. A formula may be identified that is associated with the element of the graph network. The formula may be automatically recompiled and values for the element of the graph network, and nodes and edges that share a path with the element, may be automatically recalculated using the recompiled formula.

Read-write network visualization

A system and method are disclosed for solving a hierarchy of objective functions using one or more hierarchical optimizations using explanation data stored in a database according to the one or more hierarchical optimizations, retrieving the explanation data, generating a response to a query for a goal violation by parsing the retrieved explanation data, and displaying the response.

System and method of root cause analysis of objective violations and query analysis

A system and method is disclosed for solving supply chain planning problems. The system includes a database that stores data representing a planning problem of a supply chain network and a computer that accesses the planning problem of the supply chain network stored in the database and models the planning problem as a network of nodes and edges. The computer further generates a hierarchical linear programming solution of the planning problem and applies advanced heuristics to the generated hierarchical linear programming solution. The computer still further formulates a mixed integer program to generate an optimized global hierarchical solution and stores the generated optimized global hierarchical solution in the database.

System and method for solving large scale supply chain planning problems with integer constraints

A system including a computer solves supply chain campaign planning problems involving major and minor setups. The computer is configured to execute a major campaign for two or more of a plurality of major product families and fix an optimal major product family to a major time period on a planning horizon, based at least on aggregated major productivity fractions and calculated second moments of a plurality of two or more major product families. The computer is further configured to execute a minor campaign for two or more minor product families associated with the optimal major product family, obtain a minor productivity fraction of a campaignable resource for the minor product family over at least a portion of a major time period and fix an optimal minor product family from the two or more minor product families to a minor time period based at least on the minor productivity fraction.

System and method of solving supply chain campaign planning problems involving major and minor setups

A system and method is disclosed for solving supply chain planning problems. The system includes a database that stores data representing a planning problem of a supply chain network and a computer configured to access the planning problem of the supply chain network stored in the database and model the planning problem as a network of nodes and edges. The computer is further configured to generate a hierarchical linear programming solution of the planning problem and apply advanced heuristics to the generated hierarchical linear programming solution. The computer is still further configured to formulate a mixed integer program to generate an optimized global hierarchical solution and store the generated optimized global hierarchical solution in the database.

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Bengaluru, India

Narasimha Kamath