Vehicle Routing Optimization Through Adaptive Route Subset Selection
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Solution Overview
Problem
The vehicle routing problem involves a combinatorial optimization challenge where finding an optimum solution within a practically feasible computational time is difficult due to the large number of possible routes, and selecting improper routes can lead to low-quality solutions.
Innovation Solution
An information processing apparatus and method that generates proper routes as a subset for optimization using metaheuristic algorithms, such as simulated annealing, to identify and remove unlikely routes, iteratively refining the solution until a high-quality quasi-optimum solution is achieved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all possible routes are considered in the optimization process, then the solution quality is improved, but the computational time becomes excessively long
Solution Approach 1:
The patent segments the complete set of possible routes into two subsets: proper routes (likely to be used) and improper routes (unlikely to be used). This segmentation is achieved by pre-selecting routes based on heuristics or historical data. The optimization process then focuses only on the proper routes subset, reducing computational complexity while maintaining solution quality.
Solution Approach 2:
The patent performs preliminary route selection before the main optimization process. By pre-identifying and filtering proper routes in advance, the system prepares a reduced search space that contains the most promising candidates. This preliminary action eliminates obviously suboptimal routes, allowing the subsequent optimization to converge faster to high-quality solutions.
2Loss of time
If proper routes are selected in advance to reduce computational burden, then the computational time is reduced, but the solution quality may deteriorate if improper routes are selected
Solution Approach 1:
The patent incorporates feedback mechanisms to evaluate and refine the proper routes subset. During the optimization process, performance feedback from evaluating candidate routes is used to adjust the selection criteria for proper routes. This feedback loop ensures that the pre-selected proper routes subset maintains high solution quality by incorporating lessons learned from the optimization process itself.
Solution Approach 2:
The patent dynamically adjusts parameters related to route selection and evaluation during the optimization process. By changing thresholds, weights, or selection criteria based on observed performance, the system adapts the proper routes subset to maintain solution quality while keeping computational effort manageable.
Data Source
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AI summary
An apparatus includes a processor to generate routes for delivering packages in a vehicle routing problem, obtain a first optimum solution of the vehicle routing problem with respect to the routes, determine whether a difference between an objective function value of the first optimum solution and an objective function value of a second optimum solution is greater than or equal to a first threshold value, the second optimum solution being obtained for a linear relaxation problem of the vehicle routing problem, and remove routes for which a variable indicative of a corresponding route is less than or equal to a second threshold value in the second optimum solution, upon finding that the difference is greater than or equal to the first threshold value, wherein a processor generates new routes for delivering packages other than packages that are to be delivered by one or more routes which are left remaining.