Electronic Device Allocation via Mahalanobis Distance
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Solution Overview
Problem
Conventional randomization methods for routing electronic requests to multiple electronic devices often result in covariate imbalance, requiring repeated randomization processes that consume vast computing power and are not timely.
Innovation Solution
An electronic device allocation system that balances the distribution of electronic requests among multiple devices by using Mahalanobis Distance to determine the probability of reassigning devices between groups, ensuring balanced distribution without excessive computing power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If standard randomization method is used to route electronic requests to multiple electronic devices, then the routing process is simple and fast, but covariate imbalance occurs leading to uneven distribution of requests among devices
Solution Approach 1:
The patent changes the parameter of allocation methodology from simple randomization to Mahalanobis distance-based allocation. This parameter change enables balanced distribution of covariates across treatment and control groups while maintaining computational efficiency through a single allocation process rather than repeated randomization.
Solution Approach 2:
The patent introduces Mahalanobis distance as an intermediary metric to measure the similarity between electronic devices based on their covariates. This intermediary enables the system to objectively assess and balance the distribution of devices across groups, resolving the covariate imbalance problem without requiring complex iterative procedures.
2Manufacturing precision
If repeated standard randomization processes are performed to achieve desired balance, then distribution balance improves, but computing power consumption increases vastly and timeliness deteriorates
Solution Approach 1:
The patent performs the balancing action in advance through a single Mahalanobis distance-based allocation process. By calculating the Mahalanobis distance once and assigning devices to groups based on this pre-computed metric, the system achieves balanced distribution without requiring repeated randomization processes, thereby significantly reducing computing power consumption and improving timeliness.
3Manufacturing precision
If repeated standard randomization processes are performed to achieve desired balance, then distribution balance improves, but processing time increases making the process not timely
Solution Approach 1:
The patent performs the balancing action in advance through a single Mahalanobis distance-based allocation process. By calculating the Mahalanobis distance once and assigning devices to groups based on this pre-computed metric, the system achieves balanced distribution without requiring repeated randomization processes, thereby significantly reducing computing power consumption and improving timeliness.
Solution Approach 2:
The patent replaces the mechanical iterative randomization process with a mathematical calculation approach using Mahalanobis distance. This substitution eliminates the need for repeated trial-and-error randomization cycles, reducing processing time while maintaining distribution balance through a single computational pass.
Data Source
AI summary
An advisor distribution system may include an advisor management system, which may include various software modules. The advisor management system may allow for a balanced distribution of a plurality of advisors operating a plurality of advisor computing devices into multiple groups based on value of a Mahalanobis Distance between each covariate of the plurality of advisors operating the plurality of advisor computing devices.