Smoothing-Based Optimization Termination
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Solution Overview
Problem
Optimization procedures often terminate prematurely or excessively due to lack of information on optimal parameters, leading to inaccurate results and inefficient resource utilization.
Innovation Solution
Implementing a smoothing-based stopping criterion that applies a smoothing technique to the rate of change of the best parameterization value to determine when to terminate the optimization procedure, using a calibration procedure to identify convergence criteria and reduce processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the optimization procedure uses a fixed number of iterations, then the computation time is predictable, but the result accuracy may be insufficient due to premature termination
Solution Approach 1:
The patent applies a dynamic termination criterion based on smoothing the rate of change of the objective function. Instead of using a fixed iteration count, the optimization procedure adapts its termination decision by calculating a smoothed rate of change and comparing it to a threshold, allowing the process to continue or terminate based on actual convergence behavior rather than predetermined limits
Solution Approach 2:
The patent implements feedback by continuously monitoring the rate of change of the objective function during iterations and using this information to control termination. The smoothed rate of change serves as feedback that informs whether the optimization has converged sufficiently, creating a closed-loop control system that adjusts termination based on performance metrics
2Measurement precision
If the optimization procedure runs for many iterations to ensure accuracy, then the result precision improves, but the resource utilization becomes inefficient
Solution Approach 1:
The patent uses dynamic termination criteria that adapt to the convergence behavior of the optimization process. By smoothing the rate of change and comparing it to a threshold, the system dynamically determines when sufficient accuracy has been achieved, preventing unnecessary continued iterations that would waste computational resources
Solution Approach 2:
The optimization procedure monitors its own convergence characteristics and makes autonomous termination decisions based on its performance. The system serves itself by evaluating its own rate of change and determining when to stop, eliminating the need for external intervention or arbitrary iteration limits
3Productivity
If the optimization procedure terminates early to save resources, then the resource efficiency improves, but the result accuracy deteriorates due to premature termination
Solution Approach 1:
The patent implements feedback control by continuously evaluating the smoothed rate of change of the objective function. This feedback mechanism ensures that termination only occurs when the rate of change indicates sufficient convergence, preventing premature termination while avoiding unnecessary iterations, thus balancing accuracy and efficiency
Data Source
AI summary
A device may perform an iteration of an optimization procedure. The device may apply a smoothing technique to a value relating to the optimization procedure after performing the iteration of the optimization procedure. The device may selectively terminate the optimization procedure based on applying the smoothing technique to the value relating to the optimization procedure. The device may provide information identifying a result of the optimization procedure based on selectively terminating the optimization procedure.