Order Sorting Layout Using Weight-Based Destination Assignment
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Solution Overview
Problem
In robot sorting systems with scattered compartments, randomly selecting compartments as destinations can lead to increased travel distances and path conflicts for robots, especially at hotspot destinations with high order volumes.
Innovation Solution
An order sorting method that establishes a correspondence between compartments and destinations based on compartment and destination weights, where compartment weight is inversely proportional to distance from the sorting station and destination weight is proportional to order volume, optimizing the assignment of orders to reduce travel distance and path conflicts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If compartments are scattered inside the planned site and any compartment is randomly selected as destination, then the sorting system can handle multiple destinations, but the robot travel distance increases and path conflicts occur
Solution Approach 1:
The patent changes the parameter selection criterion from random selection to weight-based selection. Each compartment is assigned a weight based on its distance from the sorting station (compartment weight = k/distance), and each destination has a weight based on order volume (destination weight = order volume). This parameter transformation enables optimized compartment-destination matching that reduces robot travel distance while maintaining multi-destination capability.
Solution Approach 2:
The patent performs preliminary calculation of compartment weights and destination weights before the actual sorting process. By pre-comparing these weights and establishing optimal correspondences in advance, the system determines the best compartment-destination pairs before robots begin traveling, thereby minimizing travel distance and avoiding path conflicts during operation.
2Ease of operation
If compartments are scattered inside the planned site and random selection is used, then the system can operate with existing layout, but path conflicts and congestion occur at hotspot destinations
Solution Approach 1:
The patent introduces weight parameters to transform the random selection process into a deterministic optimization process. By calculating compartment weights (inversely proportional to distance) and destination weights (proportional to order volume), the system reliably matches compartments to destinations, reducing path conflicts and congestion at hotspot destinations while maintaining operational simplicity through automated weight-based assignment.
Solution Approach 2:
The patent uses order volume information as feedback to determine destination weights. High-demand destinations (hotspots) receive higher weights, which influences the compartment-destination matching to allocate nearby compartments to these destinations. This feedback mechanism dynamically adjusts resource allocation based on actual demand patterns, reducing congestion and improving reliability.
3Productivity
If compartment weight is based on distance from sorting station, then nearby compartments are prioritized, but the system complexity increases
Solution Approach 1:
The patent transforms the sorting optimization problem into a parameter comparison task. By defining compartment weight as k/distance and destination weight as order volume, the complex optimization problem becomes a straightforward weight-matching process. The system calculates these weights and matches compartments to destinations by comparing weights, which simplifies the computational complexity while improving sorting efficiency and reducing robot travel distance.
Data Source
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AI summary
An order sorting method. The order sorting method is used for a sorting system, and comprises: acquiring a plurality of target orders, destination information of each target order and a compartment weight of each compartment in a sorting area, wherein the compartment weight is inversely proportional to the distance from the compartment to a sorting station; on the basis of the destination information of each target order, compiling statistics on the number of orders of each destination, so as to obtain a destination weight of each destination, wherein the destination weight is proportional to the number of orders; according to each compartment weight and each destination weight, determining a correlation between each compartment and each destination; and according to the correlation, sending a sorting instruction to a sorting robot, so as to drive the sorting robot to respectively sort each target order to the corresponding compartment on the basis of the destination information of each target order. Further comprised are an order sorting apparatus, a computing device and a computer-readable storage medium.