Route Planning Perimeter Search for Multi-Point Optimization
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Solution Overview
Problem
Existing mapping technologies fail to efficiently generate routes that incorporate multiple points of interest while minimizing travel commitment, such as time and distance, without causing excessive computational delay.
Innovation Solution
A computer-implemented method that identifies a perimeter around the origin and destination locations to select specific locations for each point of interest, rearranges the order of visiting these points, and includes newly selected locations to optimize the route, using an elliptical perimeter to efficiently search for potential locations and calculate travel commitments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing mapping technologies generate routes incorporating multiple points of interest, then the route includes more destinations, but the computational delay increases excessively
Solution Approach 1:
The patent segments the route planning process into distinct phases: identifying a preliminary route first, then separately identifying points of interest along that route. This segmentation allows the system to handle the complex multi-point route generation in manageable steps, reducing overall computational delay while maintaining route customization capability
Solution Approach 2:
The patent performs preliminary actions by first establishing a base route between origin and destination before adding points of interest. This preliminary route serves as a foundation that constrains subsequent point-of-interest selection to locations along or near the established path, significantly reducing the search space and computational requirements
2Manufacturing precision
If the system searches all potential locations for points of interest, then the route optimization is thorough, but the computational complexity increases
Solution Approach 1:
The patent applies local quality by focusing the search for points of interest only in specific locations along the preliminary route, rather than searching all potential locations globally. This localized approach maintains route optimization quality by considering only relevant points of interest that actually lie on or near the travel path, while dramatically reducing computational complexity
Solution Approach 2:
The patent uses partial action by identifying a limited set of points of interest along the preliminary route rather than exhaustively evaluating all possible points of interest. This partial evaluation approach provides sufficient route optimization for practical purposes while avoiding the excessive computational complexity of complete enumeration
Data Source
AI summary
A computer-implemented method for identifying a route that is configured to travel through multiple points of interest includes receiving a query that includes an origin location, a destination location, and at least a first point of interest and a second point of interest. The method also includes identifying a perimeter that surrounds the received origin and destination locations in response to the query. The perimeter is then used to identify a set of locations for each of the first and second points of interest.