Warehouse Storage Ranking Algorithm for Bin Selection
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Solution Overview
Problem
Current warehouse management systems face significant processing burdens in identifying suitable storage bins, often failing to place stock in the best available bin when the optimal option is not available, leading to inefficiencies in storage and rearrangement processes.
Innovation Solution
A system that ranks storage combinations based on their distance from optimality, allowing for the identification of the best available storage bin by iterating through a sorted data structure and facilitating rearrangement opportunities by comparing current rankings with potential improvements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system iterates through all possible storage combinations (A×B×C) to identify a destination bin, then the availability of storage locations is thoroughly checked, but the processing burden increases significantly
Solution Approach 1:
The patent pre-calculates and stores optimal storage combinations in a sorted data structure before transactions occur. This preliminary action eliminates the need to iterate through all A×B×C combinations during actual storage operations, reducing processing time while maintaining reliability of finding available storage locations.
Solution Approach 2:
The patent segments the storage facility into hierarchical levels (storage types, storage sections, bin types) and creates a sorted data structure that organizes combinations by their optimality rank. This segmentation allows the system to search through organized segments rather than brute-forcing all combinations, improving both speed and reliability.
2Productivity
If the system stops at the first available bin found during iteration, then processing time is reduced, but the storage efficiency decreases as the optimal bin may not be selected
Solution Approach 1:
The system pre-sorts all storage combinations by their optimality rank in advance. This preliminary sorting ensures that when the system searches for available bins, it encounters them in order of optimality, guaranteeing that the first available bin found is indeed the best option, thus maintaining both speed and optimization reliability.
Solution Approach 2:
The patent changes the search parameter from arbitrary iteration order to rank-based order. By organizing combinations according to their optimality ranking rather than simple iteration through A×B×C, the system ensures that stopping at the first available bin yields the optimal storage location, resolving the contradiction between speed and optimization quality.
3Reliability
If the system performs deep iteration through all alternatives to ensure optimal bin selection, then storage efficiency is improved, but the processing burden increases
Solution Approach 1:
The patent performs the time-consuming sorting and organization of storage combinations by optimality rank in advance, before actual storage transactions occur. This preliminary action moves the computational burden to a non-critical time period, ensuring that during actual storage operations, the system can quickly find optimal bins without significant processing delays.
Data Source
AI summary
A system and method to improve storage efficiency in a warehouse. Storage combinations are assigned a ranking base on the distance from optimal storage. After sorting the data structure base on the ranking a best available storage combination can be identified by iterating the table in a rank order. In one embodiment, the ranking is used to identify candidates for rearrangement. By comparing the best available ranking with the current ranking, greater differences reflect greater benefit of rearrangement.