Optimization Support Using Intermediate Expressions for Solution Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing optimization systems face challenges in easily selecting a suitable solution for a given optimization problem due to differences in expression methods and notation, making it difficult to match problems with appropriate solutions.
Innovation Solution
An optimization support device and method that converts information about a problem into an intermediate expression, allowing for the selection of a suitable solution based on this expression, using machine learning models to normalize and align notations, and then selecting solutions from a database of associated features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing optimization systems directly match problems with solutions using original expressions, then the system structure remains simple, but the ability to accurately match problems with suitable solutions deteriorates due to differences in expression methods and notation
Solution Approach 1:
The patent introduces an intermediate expression as a mediator between the original problem expression and the solution matching process. The conversion unit transforms the original problem expression into a standardized intermediate expression that eliminates notation differences, enabling accurate matching without requiring direct comparison of diverse original expressions. This intermediary layer resolves the contradiction by decoupling the input diversity from the matching precision requirement.
Solution Approach 2:
The patent applies parameter changes by transforming the problem expression from its original form with various notations into a standardized intermediate form. The conversion unit modifies the expression parameters (notation, format, symbols) into a unified representation, allowing solutions to be matched based on semantic content rather than surface-level expression differences, thereby improving matching accuracy while maintaining manageable system complexity.
2Measurement precision
If the system converts all problem information into intermediate expressions, then solution matching accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The patent extracts only the essential features and semantic content from the original problem expression to create the intermediate expression, rather than performing exhaustive analysis of all possible expression variations. The conversion unit identifies and extracts key problem characteristics (objective function type, constraints, variables) and represents them in the standardized intermediate form, achieving accurate matching with reduced processing overhead by focusing on essential elements only.
Data Source
AI summary
An optimization support device includes an acquisition unit, a conversion unit, a selection unit, and an output unit. The acquisition unit acquires information regarding a problem to be optimized. The conversion unit converts the information regarding the problem to be optimized into an intermediate expression representing a feature of the information regarding the problem to be optimized. The selection unit selects a solution to be applied to the problem to be optimized from the solutions associated with the intermediate expression representing the feature of the problem suitable for application based on the converted intermediate expression for decision making. The output unit outputs information regarding the selected solution.