Cargo Sorting Allocation Using Multi-Dimensional Order Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional cargo sorting methods in warehouse logistics are inefficient, particularly when handling a large number of orders, as they often allocate orders to sorting units based on a minimum number of order forms, leading to low sorting efficiency.
Innovation Solution
A method and apparatus that acquire and analyze order forms to determine the number of order forms, types of cargo, and coincidence number of types of cargo between the order form and target sorting units, selecting the most suitable unit based on these criteria to allocate and sort the cargo efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If orders are allocated to sorting units based on minimum number of order forms, then the allocation process is simple, but the sorting efficiency is low
Solution Approach 1:
The patent changes the allocation parameters from simple order form count to multiple dimensions including cargo type coincidence number, number of order forms, and number of cargo types. This multi-parameter evaluation system resolves the contradiction by providing more comprehensive allocation criteria that improve sorting efficiency while maintaining manageable system complexity through structured computation.
Solution Approach 2:
The patent replaces manual or simple mechanical allocation methods with an automated computer-based system that computes coincidence numbers and evaluates multiple sorting units. This substitution resolves the contradiction by handling the increased computational complexity through automation, thereby improving sorting efficiency without requiring manual intervention in the complex evaluation process.
2Productivity
If multiple criteria are used to select target sorting unit, then the sorting efficiency is improved, but the computation complexity increases
Solution Approach 1:
The patent performs preliminary computation of the coincidence number between cargo types in order forms and sorting units before the actual allocation decision. By pre-calculating these matching metrics for all candidate sorting units, the system resolves the contradiction by organizing the computational complexity in advance, making the final selection process more efficient and manageable.
Solution Approach 2:
The system automatically computes and compares multiple criteria (coincidence number, order form count, cargo type count) for each sorting unit without external intervention. This self-service computation approach resolves the contradiction by handling the computational complexity internally through standardized algorithms, allowing the multi-criteria evaluation to improve sorting efficiency while maintaining systematic control over the computation process.
Data Source
AI summary
A method and a device for sorting cargo. The method includes: acquiring a to-be-allocated order; determining, for each target sorting unit, at least one of: a number of to-be-sorted orders of the target sorting unit, a number of types of to-be-sorted cargo, or a coincidence number of types of cargo between the target sorting unit and the to-be-allocated order; selecting a target sorting unit based on at least one of following items of each target sorting unit: the number to-be-sorted orders, the number of types of to-be-sorted cargo, or the coincidence number of types of cargo; and allocating the to-be-allocated order to the selected target sorting unit, such that the selected target sorting unit sorts out the cargo indicated by the to-be-allocated order.