Supply Chain Plan Incremental Adjustment System
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Solution Overview
Problem
Conventional supply chain management systems struggle to efficiently re-optimize supply chain plans in response to rapid perturbations such as new demands, capacity changes, and inventory fluctuations, due to the long runtime of optimization algorithms and the infrequent generation of supply chain plans.
Innovation Solution
A system and method for incrementally adjusting supply chain plans by receiving perturbations between scheduled planning sessions, accessing data from a database, and communicating adjusted plans to supply chain entities, allowing for real-time optimization and feasibility adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional optimization algorithms are used to generate supply chain plans, then the quality of optimization is improved, but the runtime is excessively long (10-12 hours)
Solution Approach 1:
The patent divides the supply chain planning problem into multiple smaller sub-problems or modules that can be solved independently and in parallel. This segmentation allows the optimization to be performed on smaller data sets, reducing the overall runtime while maintaining solution quality through iterative refinement of the segmented results into a complete supply chain plan.
2Loss of energy
If supply chain plans are generated only during specified time intervals, then computational resources are conserved, but the system cannot respond to perturbations between planning sessions
Solution Approach 1:
The patent performs preliminary computations and pre-calculates certain aspects of the supply chain plan during the scheduled planning session. This preliminary action creates a baseline plan that can be quickly adjusted later when perturbations occur, reducing the need for full re-optimization and enabling faster response to changes between planning sessions.
Solution Approach 2:
The system implements a feedback mechanism where perturbations detected between planning sessions trigger targeted re-optimization of affected plan elements. This feedback loop allows the system to respond adaptively to changes while maintaining computational efficiency by only re-processing the necessary portions of the plan rather than the entire plan.
3Speed
If the runtime of optimization is reduced, then the system can respond faster to perturbations, but the quality of optimization deteriorates
Solution Approach 1:
The patent employs dynamic optimization approaches where the level and type of optimization performed adapts based on the nature and magnitude of perturbations. For minor perturbations, faster but less comprehensive adjustment methods are used, while significant perturbations trigger more thorough optimization. This dynamic approach maintains quality where needed while improving speed for routine adjustments.
Data Source
AI summary
A system and method is disclosed for incrementally adjusting a supply chain plan. The system includes a database operable to store data associated with one or more supply chain entities and a server system coupled with the database. The server system receives one or more perturbations in supply chain plan inputs from one or more of the supply chain entities, wherein the perturbations are received during a period of time separating a supply chain planning session from a subsequent supply chain planning session and accesses the data stored in the database associated with the one or more supply chain entities. The server system also incrementally and optimally adjusts the supply chain plan based on the one or more received perturbations and the data stored in the database and communicates the incrementally adjusted supply chain plan to the one or more supply chain entities.