Portfolio Optimizer Translation Layer for Valuated Dependencies
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Solution Overview
Problem
Current portfolio optimization approaches fail to effectively consider valuated dependencies, leading to complexity, risk of defects, and increased efforts when modifying existing optimizers to support these dependencies.
Innovation Solution
A method and system that translate original elements and dependencies into substitutive elements based on valuated dependencies, allowing the existing portfolio optimizer to operate without modification, and then translate optimization results back into original elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing portfolio optimizer is modified to support valuated dependencies, then functionality is improved, but complexity and risk increase
Solution Approach 1:
The patent introduces a translation layer that converts valuated dependencies into logical dependencies, allowing the existing portfolio optimizer to process valuated dependencies without internal modification. This intermediary translation mechanism adds functionality while isolating the core optimizer from complexity increases.
Solution Approach 2:
The solution separates the portfolio optimization problem into two independent stages: (1) translation of valuated dependencies into logical dependencies, and (2) execution by the existing portfolio optimizer. This segmentation allows each component to remain simple while the system as a whole gains enhanced functionality.
2Adaptability or versatility
If existing portfolio optimizer is modified to support valuated dependencies, then functionality is improved, but risk of defects increases
Solution Approach 1:
The translation layer acts as a buffer that prevents direct modification of the proven portfolio optimizer code. By translating valuated dependencies into the logical dependency format the optimizer already handles reliably, the system gains new functionality while preserving the reliability of the core optimization engine.
Solution Approach 2:
The patent performs preliminary translation of valuated dependencies into logical dependencies before passing them to the portfolio optimizer. This advance conversion ensures that the optimizer receives input in its expected format, preventing runtime errors and maintaining functional reliability.
3Adaptability or versatility
If existing portfolio optimizer is modified to support valuated dependencies, then functionality is improved, but development efforts increase
Solution Approach 1:
The translation mechanism serves as a reusable intermediary component that handles all valuated dependency conversions. Once implemented, this translation layer can process various types of valuated dependencies without requiring further modifications to the core optimizer, significantly reducing ongoing development efforts.
Solution Approach 2:
The translation layer is designed to handle multiple types of valuated dependencies (resource, duration, benefit) through a unified approach. This universal translation mechanism can accommodate different dependency types without requiring separate modification paths, improving development efficiency.
Data Source
AI summary
Adapting an existing portfolio optimizer to support one or more valuated dependencies without modifying the existing portfolio optimizer, may include translating one or more original elements and associated dependencies in a portfolio to be optimized based on said one or more valuated dependencies; invoking the existing portfolio optimizer with the translated one or more original elements and associated dependencies; and translating optimization results, if said optimization results contain translated one or more original elements, into a solution characterized in terms of said one or more original elements.