Large Neighborhood Search Routing With Parallel Cost Matrix Updates
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Solution Overview
Problem
Existing path optimization algorithms face challenges in calculating optimal routes with multiple nodes, especially when cost and time have an inversely proportional relationship, and they struggle with varying conditions beyond fixed waypoints.
Innovation Solution
A method using Large Neighborhood Search (LNS) that involves distributing optimal route calculations across multiple thread modules, each optimizing different cost-related factors like fuel consumption and carbon emissions, and applying a Destroy-Repair process to update cost matrices dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of nodes in the route increases, then the route coverage and complexity increase, but the calculation time increases exponentially
Solution Approach 1:
The patent divides the route optimization problem into multiple independent thread modules, each handling different optimization targets (time, distance, cost). This segmentation allows parallel processing of route calculations, reducing the exponential calculation time while maintaining comprehensive route coverage across multiple nodes.
Solution Approach 2:
The patent implements dynamic cost matrix updates during the LNS destroy-repair process. The cost matrix is recalculated based on current route segments and optimization targets, enabling adaptive optimization as the route evolves through iterative destruction and repair operations.
2Adaptability or versatility
If multiple optimization targets are applied simultaneously, then the route optimization comprehensiveness improves, but the calculation complexity increases
Solution Approach 1:
The patent segments the optimization problem into separate thread modules, each dedicated to a specific optimization target (minimum time, shortest distance, minimum cost). This modular approach allows comprehensive multi-target optimization while managing complexity through independent, specialized processing units that can operate in parallel.
Solution Approach 2:
The patent changes the optimization parameter dynamically by selecting different cost matrix configurations for different thread modules. Each thread module uses a cost matrix tailored to its specific optimization target, allowing comprehensive optimization across multiple parameters without requiring a single complex unified algorithm.
3Ease of manufacture
If fixed waypoints are used for route optimization, then the route constraints are simplified, but the adaptability to varying conditions is reduced
Solution Approach 1:
The patent implements dynamic cost matrix updates that adapt to varying route conditions and optimization targets. The cost matrix is recalculated during the LNS process based on current route segments, allowing the system to handle varying conditions (different cost structures, time constraints, distance requirements) without being limited to fixed waypoints.
Solution Approach 2:
The patent creates a universal route optimization system that can handle multiple optimization targets and varying conditions through the same LNS framework. The cost matrix serves as a universal interface that can be configured for different scenarios (time, distance, cost), making the system adaptable to various conditions while maintaining a consistent optimization approach.
Data Source
AI summary
A method for calculating an optimal route includes selecting first and second optimization targets; distributing optimal route calculation of the first and second optimization targets to first and second thread modules, respectively; calculating a cost matrix between nodes or receiving the cost matrix from a database when calculating an optimal route according to the LNS by applying the first and second optimization targets; randomly arranging nodes of a starting point, an arrival point and stopovers, and executing the optimal route calculation according to the LNS based on the cost matrix between the arranged nodes; and selecting an optimal route that satisfies a predetermined condition according to the first and second optimization targets calculated in the optimal route calculation. The optimal route calculation is executed by updating the cost matrix between two nodes connected by destruction and repair of the LNS into a cost matrix corresponding to the optimization target.