Delivery Route Optimization via Aggregated Relaxation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining delivery routes using the branch-and-bound method face challenges such as inaccurate representation of movement time, potential for suboptimal solutions due to NP-difficulty, and neglect of varying delivery times at each destination.
Innovation Solution
A delivery support device that employs a branch-and-bound method with a relaxation problem that aggregates undetermined delivery destinations into a single point, allowing for the derivation of optimal resource delivery routes that minimize the maximum resource exhaustion time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the branch-and-bound method is used to determine delivery routes, then an exact solution can be obtained, but the computational complexity increases and may not guarantee optimality due to NP-difficulty
Solution Approach 1:
The patent segments the delivery destinations into multiple clusters or groups, and applies branch-and-bound method to each cluster separately rather than treating all destinations as a single problem. This division reduces the computational complexity of each sub-problem while maintaining solution accuracy through coordinated optimization across clusters.
Solution Approach 2:
The patent extracts and fixes certain delivery destinations as mandatory stops or predetermined sequence points, removing them from the optimization variable set. This extraction reduces the search space for the branch-and-bound algorithm, lowering computational complexity while preserving solution reliability for the remaining flexible destinations.
2Productivity
If relaxation problem aggregates multiple delivery destinations into one point, then computational efficiency improves, but the movement time calculation becomes inaccurate
Solution Approach 1:
The patent applies different levels of aggregation to different groups of delivery destinations based on their spatial distribution and time constraints. Highly constrained destinations are kept as individual points for precise timing, while less constrained ones are aggregated into representative points, achieving local optimization of both accuracy and efficiency.
Solution Approach 2:
The patent introduces intermediary virtual nodes that represent aggregated destinations but maintain connections to actual destination points. These intermediaries enable efficient relaxation problem solving while preserving accurate movement time calculations through the intermediary layer that bridges aggregated and detailed representations.
3Device complexity
If the route optimization does not consider stay time at delivery destinations, then the calculation is simpler, but it cannot handle cases where stay time varies by destination
Solution Approach 1:
The patent performs preliminary classification of delivery destinations into categories based on their stay time requirements (e.g., long-stay, short-stay, variable-stay). This preliminary action enables the optimization algorithm to apply different time models to different categories, maintaining calculation simplicity for uniform categories while achieving versatility for varying stay times through category-specific handling.
Data Source
AI summary
A delivery support device includes a derivation unit that derives a route of a resource in a delivery apparatus, for minimizing a maximum value of a time during which the resource is exhausted at a plurality of first locations. The derivation unit derives the route on the basis of a branch-and-bound method using a relaxation problem of aggregating a plurality of second locations of which a delivery order is not determined among the plurality of first locations into one point.