Fast Planning Heuristic for Batch and Interactive Planning

a planning and interactive technology, applied in the field of supply chain planning, can solve the problems of inability to re-optimize, adjust the supply chain plan, and entities cannot achieve ad hoc changes that are not optimal, and achieve the effect of reducing one or more flowpaths

Inactive Publication Date: 2019-08-01
BLUE YONDER GRP INC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This approach significantly reduces the time required to generate and adjust supply chain plans, enabling real-time optimality and feasibility, improving the speed and quality of supply chain management.

Problems solved by technology

However, traditional optimization algorithms require a representation of the complete supply chain plan in memory, which is a latency and is undesirable because it wastes valuable time resources in creating a huge in memory model of the complete supply chain.
This traversal is repeated unnecessarily for each pass of the optimization algorithm, which is a latency and is undesirable.
In addition, because of the complexity and the amount supply chain data stored in memory, a typical run-time for generating an optimal supply chain plan may be, for example, 10-12 hours.
However, shortly after, if not immediately after, the supply chain plan is generated and distributed to the other entities within the supply chain network, various perturbations (i.e., changes or events) often occur that renders the generated supply chain plan infeasible.
In addition, because the supply chain plan is only generated during specified time intervals and the run-time is significant in duration (i.e., 10-12 hours), the entity is not able to re-optimize, or otherwise adjust the supply chain plan to a state of feasibility, until the next specified time interval.
As a result, conventional efforts to re-optimize or otherwise adjust the supply chain plan to a state of feasibility, often involves ad hoc changes that are not optimal.
In addition, conventional efforts to reduce the duration of the run-time are disadvantageous, because the speed of optimization is typically incompatible with the quality of the optimization.
That is, these conventional efforts to reduce the duration of the run-time adversely affect the quality of the adjustments to the supply chain plan.
This inability to reduce the duration of the run-time and to re-optimize or otherwise adjust the supply chain plan to a state of feasibility, based on these perturbations is undesirable.

Method used

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  • Fast Planning Heuristic for Batch and Interactive Planning
  • Fast Planning Heuristic for Batch and Interactive Planning
  • Fast Planning Heuristic for Batch and Interactive Planning

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Embodiment Construction

[0017]Reference will now be made to the following detailed description of the preferred and alternate embodiments. Those skilled in the art will recognize that the present invention provides many inventive concepts and novel features, that are merely illustrative, and are not to be construed as restrictive. Accordingly, the specific embodiments discussed herein are given by way of example and do not limit the scope of the present invention.

[0018]FIG. 1 illustrates an exemplary system 100 according to a preferred embodiment. System 100 comprises a supply chain planner 110, supply chain network 120, a network 130, and communication links 132 and 134a-134n. Although a single supply chain planner 110, a single supply chain network 120, and a single network 130, are shown and described; embodiments contemplate any number of supply chain planners 110, any number of supply chain networks 120, and / or any number of networks 130, according to particular needs. In addition, or as an alternativ...

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Abstract

A system and method is disclosed for incremental planning using a list based heuristic. The system includes a database storing supply chain entity data and a server system coupled with the database. The server system receives demand for one or more end items from one or more of the supply chain entities within a supply chain network and collapses the supply chain network into one or more flowpaths for each of the one or more end items. The server system also sorts the one or more flowpaths based on one or more rules or parameters stored in the database and reduces the one or more flowpaths using constraints stored in the database. The server system further generates a supply chain plan by solving the received demand using a list based heuristic stored in the database and communicates the generated supply chain plan to the one or more supply chain entities.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a continuation of U.S. patent application Ser. No. 12 / 607,043, filed on Oct. 27, 2009 and entitled “Fast Planning Heuristic for Batch and Interactive Planning,” which is a continuation-in-part (CIP) of U.S. patent application Ser. No. 12 / 043,240, filed on Mar. 6, 2008 and entitled “Sentient Optimization for Continuous Supply Chain Management,” which claims the benefit of U.S. Provisional Patent Application Ser. No. 60 / 893,428, filed Mar. 7, 2007, entitled “Incremental Planning.” U.S. patent application Ser. No. 12 / 607,043 also claims priority to U.S. Provisional Patent Application Ser. No. 61 / 109,498, filed Oct. 29, 2008, entitled “Fast Planning Heuristic for Batch and Incremental Planning.”[0002]U.S. patent application Ser. Nos. 12 / 607,043 and 12 / 043,240, and U.S. Provisional Patent Application Ser. Nos. 60 / 893,428, and 61 / 109,498 are assigned to the assignee of the present application. The subject matter disclosed in...

Claims

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Application Information

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Patent Type & AuthorityApplications(United States)
IPC IPC(8): G06Q10/08G06Q10/06
CPCG06Q10/087G06Q10/06G06Q10/063
InventorSINGH, RIPU DAMANIYER, ANAND
OwnerBLUE YONDER GRP INC