Multi-objective Optimization Weight Adjustment
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Solution Overview
Problem
Existing multi-objective optimization tools fail to accurately reflect user demands, requiring users to manually adjust parameters or edit optimization results, leading to inefficiencies and mismatched solutions.
Innovation Solution
A multi-objective optimization apparatus with a weight adjustment method and program that includes a correction accepting unit and a weight adjustment unit, using linear programming to adjust evaluation item weights based on user corrections, ensuring the objective function values are improved or maintained, and a GUI for easy user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually adjust parameters to obtain desired optimization results, then the accuracy of reflecting user demands is improved, but the ease of operation deteriorates because users need to understand complex algorithms and parameter meanings
Solution Approach 1:
The system introduces an intermediary mechanism that automatically adjusts parameters based on user corrections to the optimization results. Instead of requiring users to directly understand and adjust complex parameters, the system mediates by observing user corrections and automatically deriving appropriate parameter adjustments, thus resolving the contradiction between accuracy and ease of operation
Solution Approach 2:
The system implements feedback by monitoring user corrections to optimization results and using this feedback to automatically adjust parameters. When users correct the optimization output, the system learns from these corrections and adjusts parameters accordingly, enabling accurate reflection of user demands without requiring users to directly manipulate complex parameters
2Adaptability or versatility
If users manually edit optimization results to satisfy requirements, then the adaptability to user needs is improved, but the productivity deteriorates because the whole schedule needs to be revised and optimization re-executed
Solution Approach 1:
The system performs preliminary action by automatically adjusting parameters in response to user corrections before re-executing optimization. This preliminary parameter adjustment is based on learned patterns from user corrections, enabling the system to adapt to user needs while minimizing the need for complete re-optimization and thus maintaining productivity
Solution Approach 2:
The system uses feedback from user corrections to automatically adjust parameters and maintain optimization results. By continuously monitoring and responding to user corrections, the system adapts to user needs while avoiding the need for complete schedule revisions, thereby preserving operational efficiency
3Measurement precision
If the number of constraints is increased to improve optimization accuracy, then the measurement precision is improved, but the device complexity increases making parameter adjustment more difficult
Solution Approach 1:
The system applies self-service by automatically managing parameter adjustments based on user corrections to optimization results. Instead of requiring users to manually adjust multiple parameters in response to increased constraints, the system autonomously handles parameter tuning, thus maintaining high optimization accuracy while reducing the complexity of parameter adjustment for users
Data Source
AI summary
A multi-objective optimization apparatus provides a weight adjustment apparatus, method, and computer program product, to perform optimization while reflecting user's demands. The multi-objective optimization apparatus for adjusting weights of a plurality of evaluation items includes a correction accepting unit for accepting an operation for correcting an initial solution as one of solutions to the plurality of evaluation items, and a weight adjustment unit for adjusting weights of the plurality of evaluation items using the initial solution based on the corrected solution as a corrected initial solution.