Grid Partitioning for Delivery Routing Efficiency
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Solution Overview
Problem
Current routing and scheduling systems face challenges in efficiently calculating and storing time and distance data for large numbers of delivery locations, often exceeding processing and memory capabilities, making it a time-consuming and costly process.
Innovation Solution
A computer program product that uses grid partitioning to divide the delivery region into manageable areas, creating a traversable network with nodes and arcs, and populating a super matrix with time/distance data from each location to its friends and depots, allowing for efficient calculation and storage of shortest path information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If shortest path calculations are performed between all delivery locations using traditional routing algorithms, then complete routing information is obtained, but processing time and memory requirements become excessively high
Solution Approach 1:
The delivery region is divided into multiple grids, and the set of all delivery locations is partitioned into different groups. Shortest path calculations are performed separately for each group rather than for all locations simultaneously. This segmentation reduces the computational complexity from O(n²) to O(k·m²) where n is total locations, k is number of groups, and m is average locations per group, thereby significantly reducing processing time while maintaining routing completeness through aggregation of results from all groups.
2Measurement precision
If shortest path calculations are performed between all delivery locations, then accurate time and distance data is obtained, but memory capacity requirements exceed available resources
Solution Approach 1:
The patent extracts and stores only the essential routing information (shortest path times and distances) for locations within the same group, rather than maintaining complete pairwise information for all locations. The super matrix stores compressed routing data where each row represents a delivery location and contains only relevant time/distance values to other locations in the same group. This extraction approach maintains measurement precision for required routes while dramatically reducing memory capacity requirements.
3Area of stationary object
If the delivery area is expanded to serve more locations, then service coverage is improved, but routing calculation complexity increases exponentially
Solution Approach 1:
As the delivery area expands and more locations are added, the system automatically divides the enlarged region into additional grids and creates more groups. This segmentation strategy ensures that calculation complexity scales linearly with the number of groups rather than quadratically with total locations. Each group is processed independently using the same efficient algorithms, allowing the system to handle expanded delivery areas without exponential increases in computational complexity.
Data Source
AI summary
The present invention provides systems, methods and computer program-product for calculating and storing time and distance information in an economical and efficient manner. The time and distance information may be used in the development of traversable networks for the delivery and retrieval of items from multiple locations in a timely and efficient manner.