System Configuration Derivation Device for Large-Scale Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing system configuration optimization methods face challenges in efficiently generating optimal configurations within a reasonable time frame, especially for large-scale systems, and lack the ability to provide meaningful progress updates to users during the optimization process.
Innovation Solution
A system configuration derivation device and method that convert system optimization problems into mathematical optimization problems, reduce problem size by adding constraints, compute solutions with reduced variables, and output progress information, enabling the sequential presentation of feasible solutions and optimal configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If system configuration optimization is performed on large-scale systems using conventional mathematical optimization methods, then optimal system configurations can be obtained, but the computation time becomes unrealistically long
Solution Approach 1:
The patent divides the system configuration optimization problem into multiple sub-problems based on functional requirements. Each sub-problem corresponds to a specific functional requirement and can be optimized independently. This segmentation allows the overall optimization to be performed more efficiently by solving smaller sub-problems rather than one large complex problem, thereby reducing computation time while maintaining optimization accuracy.
2Manufacturing precision
If conventional optimization methods are used to solve system configuration problems, then optimal solutions can be found, but meaningful progress updates cannot be provided to users during the optimization process
Solution Approach 1:
The patent implements a feedback mechanism that provides progress information to users during the optimization process. As the optimization proceeds through different iterations and sub-problem solutions, the system outputs intermediate results and status updates, allowing users to monitor the optimization progress in real-time. This feedback loop maintains solution quality while addressing the information loss about optimization status.
3Productivity
If the number of variables in the mathematical optimization problem is reduced by adding constraints, then computation time is reduced, but the problem complexity increases due to additional constraints
Solution Approach 1:
The patent segments the system configuration problem into multiple sub-problems, each with fewer variables and constraints. By dividing the overall problem into smaller manageable sub-problems based on functional requirements, the computation time for each sub-problem is reduced. The segmentation strategy balances the trade-off between reducing variable count for faster computation and managing problem complexity through structured decomposition.
Data Source
AI summary
The system configuration derivation device includes an optimization problem conversion unit that converts a system optimization problem into a mathematical optimization problem, a problem size reduction unit that reduces the number of variables in the mathematical optimization problem by adding a constraint to the mathematical optimization problem, an optimization unit that computes a solution to the mathematical optimization problem with a reduced number of variables, a gradual optimization unit that sequentially outputs the solution, and progress information of a process, and a solution conversion unit that converts the solution into system configuration information, which is a solution to the system optimization problem and outputs the system configuration information and the progress information.