Quantum Route Repository for Real-Time Route Recalculation
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Solution Overview
Problem
Classical computing systems face inefficiencies in recalculating optimized routes due to the deterministic nature of classical computing, which limits their ability to adapt to real-time changes and deviations in traffic conditions.
Innovation Solution
A classical computing system leverages a quantum generated route repository to determine initial and modified optimized routes by utilizing quantum computing's probabilistic nature to calculate every permutation and combination of routes, which are then refined by classical computing to incorporate real-time context and constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If classical computing systems recalculate optimized routes using deterministic algorithms, then route optimization can be achieved, but the system cannot adapt quickly to real-time changes and deviations in traffic conditions
Solution Approach 1:
The quantum computing system performs preliminary computation of all possible route permutations and combinations before real-time changes occur. These pre-calculated routes are stored in a route repository, allowing the classical system to quickly retrieve and adapt pre-computed optimal paths when traffic conditions change, rather than recalculating from scratch.
Solution Approach 2:
The system creates copies of pre-computed quantum routes and stores them in a classical route repository. When real-time changes occur, the system can quickly copy and adapt these pre-existing route solutions rather than performing full recalculations, enabling rapid adaptation to traffic deviations while maintaining optimization quality.
2Measurement precision
If quantum computing is used to calculate all permutations and combinations of routes, then comprehensive route optimization is achieved, but the computational complexity and resource requirements increase significantly
Solution Approach 1:
The computational task is segmented into two parts: the quantum computing system handles the complex permutation and combination calculations to generate all possible routes, while the classical computing system handles route selection, filtering, and adaptation. This segmentation allows each system to operate in its optimal domain, achieving comprehensive optimization without requiring the entire system to have quantum-level complexity.
Solution Approach 2:
A route repository acts as an intermediary between the quantum computing system and the classical computing system. The quantum system generates routes and stores them in the repository, which then provides routes to the classical system for real-time adaptation. This intermediary decouples the complex quantum computation from the real-time classical decision-making, reducing overall system complexity while maintaining optimization accuracy.
3Reliability
If classical computing systems perform route recalculations, then deterministic results can be obtained, but the recalculation time increases when dealing with multiple constraints and modifications
Solution Approach 1:
The quantum computing system pre-calculates and stores all possible optimized routes considering multiple constraints before real-time changes occur. When traffic conditions change, the classical system can quickly filter and select from these pre-computed routes rather than performing time-consuming recalculations, significantly reducing recalculation time while maintaining reliable optimization results.
Solution Approach 2:
The system dynamically adapts pre-computed quantum routes by applying real-time traffic constraints to the stored route repository. Instead of static deterministic recalculation, the system dynamically filters and modifies pre-existing optimal routes based on current conditions, achieving both reliability and speed by combining pre-computed accuracy with real-time adaptability.
Data Source
AI summary
Optimizing route modification using a quantum generated route repository is provided herein. In particular, a classical computing system determines an initial route optimization request comprising at least one initial constraint. The at least one initial constraint includes a starting location and an ending location for a desired route. The classical computing system determines a plurality of initial optimized routes from a plurality of routes based on the at least one initial constraint. The plurality of routes are generated by a quantum computing system. The classical computing system determines a modified route optimization request. The modified route optimization request includes at least one modified constraint. The classical computing system determines a plurality of modified optimized routes from the plurality of routes based on the at least one modified constraint. The plurality of routes are previously generated by the quantum computing system.