Column Generation for Dynamic Vehicle Routing Optimization
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Solution Overview
Problem
Existing solution systems for vehicle routing problems (VRPs) are specialized and difficult to apply to other variations of VRPs, requiring high human resources and time, making them impractical for businesses.
Innovation Solution
An information processing program that uses a column generation method to generate routes satisfying newly set conditions, formulates a route selection problem, solves it, and outputs the solution, enabling the solution of VRPs with unknown problem settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a solution system is developed for a specific VRP variation, then it can solve that particular VRP effectively, but it cannot be applied to other VRP variations and requires high human resources and time for each new variation
Solution Approach 1:
The patent creates a universal VRP solution system that can handle multiple VRP variations through a common framework. The system uses a standardized problem definition structure that can accommodate different constraint types and objective functions, allowing a single system to solve various VRP problems without requiring separate specialized development for each variation.
Solution Approach 2:
The system handles different VRP variations by changing problem parameters and constraints rather than restructuring the entire solution approach. By parameterizing problem settings, constraints, and objective functions, the system can adapt to different VRP types through configuration rather than code modification, enabling versatility while maintaining solution reliability.
2Reliability
If a specialized solution system is developed for each VRP variation, then it can provide accurate solutions for that specific problem, but it requires high human resources and a sufficient period for development
Solution Approach 1:
The patent develops a single universal solution system that can handle multiple VRP variations, eliminating the need to create separate specialized systems for each problem type. This universal approach maintains solution accuracy while dramatically improving development productivity by reusing the same core framework across different VRP applications.
Solution Approach 2:
The system performs preliminary configuration and parameter setup to adapt to different VRP variations before solving the actual routing problem. By pre-defining problem structures, constraint templates, and solution methodologies, the system reduces the time and resources needed for each new VRP application while maintaining accurate solutions.
3Ease of manufacture
If existing VRP solution systems are used, then they can solve known VRP variations, but they are difficult to apply to VRPs with unknown or new problem settings
Solution Approach 1:
The patent employs a parameterized problem definition approach that allows the system to accommodate unknown or new VRP settings by configuring parameters rather than requiring specialized development. The system can handle new problem types by defining their parameters within the existing framework, making it both easy to apply and highly adaptable to unseen variations.
Solution Approach 2:
The patent segments the VRP solution system into modular components that can be independently configured for different problem settings. This segmentation allows the system to easily adapt to new VRP variations by combining and configuring existing modules in different ways, rather than requiring a complete redesign for each new problem type.
Data Source
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AI summary
An information processing program including instructions which, when executed by a computer, cause the computer to execute processing including: generating routes in a case where a plurality of mobile bodies that have started from a specific node passes through a plurality of nodes and returns to the specific node, which satisfy a plurality of newly set conditions related to the routes, from a set of the plurality of routes that indicates order in which the plurality of mobile bodies visit the nodes, by applying a column generation method to the set of the plurality of routes; generating a route selection problem by using the generated routes; solving the generated route selection problem; and outputting a solution result of the route selection problem.