Image-Based Analytics for Supply Chain LP Optimization
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Solution Overview
Problem
Current supply chain planning methods using linear programming (LP) are resource-intensive and often require simplifying constraints or objectives, making it difficult to analyze and improve solving speed, especially since monolithic LP problems are not amenable to standard decomposition techniques and measures of problem complexity are non-intuitive.
Innovation Solution
The implementation of an image-based analytics system that visualizes supply chain planning problems, allowing for the generation of insights into complexity and simplification of LP problems, enabling faster formulation and solution of supply chain planning issues through the use of image analyzers and visualizations that provide interactive dashboards for users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If linear programming is used to generate optimal supply chain plans, then solution optimality is improved, but resource consumption and solving time increase
Solution Approach 1:
The patent segments the monolithic LP problem into multiple smaller sub-problems that can be solved individually or in parallel. This is achieved by decomposing the supply chain planning problem into manageable components, allowing faster solving while maintaining optimality through coordinated solution integration
Solution Approach 2:
The patent introduces a new dimension of problem analysis by visualizing LP problem complexity through image-based representations. This transforms abstract complexity measures into intuitive visual formats, enabling users to understand and address complexity issues that would otherwise be non-intuitive
2Measurement precision
If monolithic LP problems are solved directly, then solution accuracy is maintained, but decomposition techniques cannot be applied
Solution Approach 1:
The patent applies segmentation by breaking down the monolithic LP problem structure into smaller, manageable sub-problems. This allows decomposition techniques to be applied while maintaining solution accuracy through proper coordination of sub-problem solutions
Solution Approach 2:
The patent introduces visualization tools as an intermediary between the complex LP problem structure and the user. This intermediary layer helps users understand and manage problem complexity without sacrificing solution accuracy
3Loss of information
If complexity measures in LP problems are used, then problem analysis is possible, but the measures are non-intuitive and provide limited user interaction
Solution Approach 1:
The patent replaces traditional numerical complexity measures with image-based visual representations. This substitution transforms abstract, non-intuitive complexity data into intuitive visual formats that users can easily interpret and interact with
Solution Approach 2:
The patent uses color-coded visualizations to represent different aspects of LP problem complexity. This allows users to quickly grasp complex information through intuitive color patterns, improving ease of operation while preserving comprehensive problem analysis capabilities
Data Source
AI summary
A system and method are disclosed for image analysis of supply chain planning problems modeled as a linear programming (LP) problems. Embodiments include receiving an LP matrix representing constraints and variables of at least a portion of a supply chain planning problem, generating a sorted variable index for the variables of the LP matrix, generating a sorted constraint index for the constraints of the LP matrix, identifying functions of the variables and the constraints, selecting one or more colors of pixels of a supply chain problem image based, at least in part, on the identified functions of the variables and constraints, selecting locations of the pixels, and displaying a visualization of the supply chain problem image.