Optimization Device for Dynamic Weighting Coefficient Adjustment
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Solution Overview
Problem
Scheduling tasks, such as determining advertisement broadcast times, require significant labor and existing technologies do not facilitate easy user-intended scheduling optimizations.
Innovation Solution
An optimization device and method that receive changes in weighting coefficients for explanatory variables in an objective function, allowing for the optimization of scheduling targets based on updated objective functions, using a computer system with a CPU, database, and communication module to generate schedule data similar to that of an expert scheduler.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual scheduling methods are used to optimize scheduling targets, then scheduling can be performed with simple systems, but considerable labor is required and scheduling efficiency is low
Solution Approach 1:
The system enables self-service optimization by automatically computing scheduling results based on user-defined objective functions and constraints. The optimization unit autonomously processes scheduling requests using the objective function computation unit, eliminating the need for manual scheduling work while maintaining simplicity in user interaction.
Solution Approach 2:
The patent replaces manual mechanical scheduling operations with automated computational systems. The objective function computation unit and optimization unit use mathematical algorithms to substitute human labor in scheduling decisions, significantly improving productivity while the modular architecture keeps system complexity manageable.
2Adaptability or versatility
If fixed objective functions are used in optimization, then the system is simple to operate, but it cannot adapt to changing user preferences and scheduling requirements
Solution Approach 1:
The system implements dynamics by allowing the objective function to be dynamically adjusted through user input. The reception unit accepts changes in weighting coefficients and constraints, enabling the objective function to adapt to evolving user preferences while maintaining a simple interface for making these adjustments.
Solution Approach 2:
The patent enables adaptability through parameter changes in the objective function. Users can modify weighting coefficients and constraints without changing the overall system structure, allowing flexible adaptation to different scheduling scenarios while keeping the operation interface simple and consistent.
3Manufacturing precision
If complex optimization algorithms are implemented to achieve precise scheduling, then scheduling precision is improved, but the system becomes difficult to operate and understand
Solution Approach 1:
The patent introduces an intermediary layer between the complex optimization algorithms and the user. The reception unit, objective function computation unit, and optimization unit act as intermediaries that handle the complexity internally while presenting a simple interface to users. Users define high-level objectives and constraints without needing to understand the underlying complex algorithms.
Data Source
AI summary
A change in a weighting coefficient for an explanatory variable in an objective function used to optimize a target is received, and the target is optimized based on the objective function to which the changed weighting coefficient has been applied.