Route Planning Algorithm Using Intermediate Nodes for Cost Efficiency
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Solution Overview
Problem
Existing algorithms for calculating the shortest path from a route to destination nodes in electronic mapping and route planning are inefficient, particularly when dealing with a large number of origin and destination nodes, as they require multiple iterations and are processor-intensive.
Innovation Solution
A computer-implemented method that identifies origin nodes based on a threshold distance from destination nodes, calculates costs to a common intermediate node, and determines the shortest path by comparing and updating costs, thereby collapsing multiple algorithm runs into a single efficient process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional algorithms (Dijkstra, Floyd-Warshall, etc.) are used to calculate shortest paths from multiple origin nodes to destination nodes, then the calculation is thorough and accurate, but the processor usage is high and the calculation time is excessive
Solution Approach 1:
The patent segments the graph into a route portion containing origin nodes and a destination portion containing destination nodes. By dividing the calculation domain and applying different algorithms to different segments (route portion vs. destination portion), the system achieves both accuracy and efficiency. The route portion uses simplified cost calculation while the destination portion uses traditional shortest path algorithms.
Solution Approach 2:
The patent applies traditional algorithms only where necessary (at the destination portion) rather than throughout the entire graph. For the route portion, it uses a simplified cost calculation approach that is less computationally intensive. This partial application of expensive algorithms reduces overall processor usage while maintaining accuracy where it matters most.
2Measurement precision
If traditional algorithms perform multiple iterations to calculate shortest paths, then the results are accurate, but the number of iterations increases processor intensity and reduces speed
Solution Approach 1:
The patent divides the graph into two segments: a route portion and a destination portion. This segmentation allows the system to use different calculation approaches for each segment, performing multiple iterations only where necessary (destination portion) while using single-pass calculations for the route portion, thereby improving speed without sacrificing accuracy.
Solution Approach 2:
Multiple iterative calculations are performed only on the destination portion of the graph where they are truly needed, rather than repeatedly processing the entire graph. The route portion uses a simplified single-pass cost calculation, reducing the total number of iterations and improving calculation speed.
3Adaptability or versatility
If the system calculates costs from all origin nodes to all destination nodes, then comprehensive route options are provided, but the computational complexity increases significantly
Solution Approach 1:
The patent segments the calculation process into two distinct phases: first calculating costs from origin nodes to intermediate nodes on the route, then calculating costs from those intermediate nodes to destination nodes. This segmentation reduces algorithmic complexity by breaking down the full matrix calculation into smaller, more manageable steps that can be optimized independently.
Solution Approach 2:
The patent introduces intermediate nodes on the route as mediators between origin nodes and destination nodes. Instead of directly calculating all origin-to-destination paths, the system uses these intermediate nodes as stepping stones, simplifying the computational graph and reducing the complexity of finding comprehensive route options.
Data Source
AI summary
Systems and methods are disclosed for determining shortest route(s) or path(s) to one or more destination nodes from one or more origin nodes. In accordance with one implementation, a computer-implemented method is provided that includes identifying a plurality of origin nodes associated with a route based on a threshold distance from at least one destination node, the origin nodes being options for a departure from the route to the at least one destination node. Further, the method may include calculating, using a processor, a cost associated with travelling from each of the origin nodes to at least one common intermediate node between the route and the at least one destination node, and determining a path to the at least one destination node based on the origin node having the lowest calculated cost.