Warehouse Picking Task Allocation for High-Density Shelves
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Solution Overview
Problem
Current automatic warehouse systems face inefficiencies in picking operations due to the inflexibility of high-density storage systems, where closely arranged shelves hinder effective task allocation and management of merchandise picking tasks.
Innovation Solution
A task allocation method and apparatus that determine merchandise picking times, order picking times, and allocate picking tasks to target shelves based on merchandise status, optimizing the selection of orders and shelves to improve picking efficiency by calculating moving and picking speeds, and ranking orders for efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If high-density storage systems with closely arranged shelves are used, then storage capacity and space utilization are improved, but picking operation flexibility deteriorates
Solution Approach 1:
The patent implements dynamic task allocation that adapts to real-time shelf statuses and order requirements. The system dynamically adjusts picking sequences and shelf selections based on current warehouse conditions, transforming the static high-density storage system into a dynamic one that maintains flexibility despite close shelf arrangement.
Solution Approach 2:
The system changes operational parameters such as picking sequences, shelf selections, and task allocation strategies based on real-time conditions. By adjusting these parameters dynamically, the system optimizes picking efficiency in the constrained high-density environment without compromising storage capacity.
2Device complexity
If traditional task allocation methods are used in high-density warehouses, then system simplicity is maintained, but picking efficiency deteriorates
Solution Approach 1:
The patent replaces traditional mechanical task allocation methods with an intelligent computing system that uses algorithms to optimize picking tasks. This substitution enables complex optimizations without proportionally increasing physical system complexity, improving picking efficiency through software-based intelligence.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor shelf statuses, order requirements, and picking progress. This feedback enables real-time adjustments to task allocation, allowing the system to adapt and optimize picking efficiency while maintaining manageable operational complexity through automated decision-making.
3Area of stationary object
If shelves are closely arranged for high-density storage, then space utilization is improved, but task allocation flexibility deteriorates
Solution Approach 1:
The patent segments the warehouse into discrete shelf units with individually trackable statuses. This segmentation allows the system to allocate tasks to specific shelves based on real-time conditions, maintaining flexibility in task allocation despite the closely arranged high-density configuration. Each shelf can be independently selected or skipped based on order requirements and availability.
Data Source
AI summary
A task allocation method and apparatus are provided. The method includes: receiving orders of merchandises stored on shelves; determining a merchandise picking time of each merchandise of the received orders; determining an order picking time for each received order according to the merchandise picking time of each merchandise; determining an order set according to the order picking time for each received order, and selecting orders from the order set as target orders; locating shelves on which merchandises in the target orders are stored; obtaining merchandise status of the merchandises in the target orders, and determining a target shelf according to the merchandise status; allocating, a picking task of the merchandises to the target shelf; determining a picking workstation corresponding to the target shelf; instructing the target shelf to move to the picking workstation to execute the picking task, and to leave the picking workstation after the picking task is completed.