Compressing Shortest Path Matrices for Delivery Route Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional shortest path matrices for delivery route optimization are excessively large, requiring significant storage space and reducing accessibility, as they are NP-hard problems that are computationally complex and inefficient for real-time processing.
Innovation Solution
A system and method for compressing shortest path matrices by reducing the number of map intersection nodes using specific compression rules, transforming initial shortest path matrices into compressed matrices that can be stored in RAM, enabling efficient delivery route determination for ecommerce website delivery orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional shortest path matrices are used for delivery route optimization, then complete path information is available, but storage space requirements become excessively large (61 terabytes for a city with 116,000 nodes)
Solution Approach 1:
The patent extracts only the essential elements needed for route optimization by removing redundant node information from the complete shortest path matrix. Instead of storing all intermediate nodes, the system extracts and stores only compressed representations that preserve the necessary routing information, significantly reducing storage requirements while maintaining optimization capability
Solution Approach 2:
The patent inverts the traditional approach by not storing complete paths and then accessing them, but rather storing compressed representations that can be decompressed on-demand. This inversion transforms the problem from storage-intensive to computation-intensive at query time, enabling the system to work with much smaller data structures
2Adaptability or versatility
If conventional shortest path matrices are stored, then all shortest paths are accessible, but real-time accessibility is reduced due to large storage size
Solution Approach 1:
The patent performs preliminary compression of the shortest path matrix into a compact format that can be quickly loaded into memory. By pre-processing the data into a compressed state, the system eliminates the time penalty of accessing large datasets, enabling real-time route optimization while maintaining adaptability to different query scenarios
Solution Approach 2:
The patent changes the parameter representation from storing complete node sequences to storing compressed numerical representations. This parameter transformation reduces the data size dramatically while preserving the ability to retrieve and interpret path information when needed, balancing accessibility with real-time performance
3Measurement precision
If complete shortest path matrices are used, then accurate delivery routes can be determined, but computational complexity increases due to NP-hard nature of the problem
Solution Approach 1:
The patent segments the complete shortest path matrix into compressed blocks or regions that can be processed independently. By dividing the problem space into manageable segments represented in compressed form, the system reduces computational complexity while maintaining the precision needed for accurate delivery route determination through selective decomposition of relevant segments
Data Source
AI summary
Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform an act of preparing an initial shortest path matrix including a plurality of elements, an initial number of a plurality of map intersection nodes, and a plurality of full shortest paths between an origination map intersection node and a destination map intersection node. Each element can include a full shortest path, and each full shortest path can include one or more map intersection nodes. The one or more processing modules also can be configured to compress the initial shortest path matrix to form a compressed shortest path matrix that includes a compressed number of the plurality of map intersection nodes that is fewer than the initial number of the plurality of map intersection nodes.