Dynamic Warehouse Storage Space Planning
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Solution Overview
Problem
Existing warehouse storage space planning methods fail to systematically utilize storage capacity and flexibly plan spaces based on actual warehouse conditions, leading to inefficient use of space and increased workload due to inaccurate estimation and lack of consideration for storage attribute parameters and changes in goods.
Innovation Solution
A method and device for warehouse storage space planning that obtain warehouse goods change information and current storage space utilization, determine storage attribute parameters, and allocate spaces based on these parameters and future storage needs, using machine learning algorithms to induce necessary parameters and optimize space usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed storage spaces are recommended only on a category basis, then storage space allocation is simplified, but storage space utilization becomes inefficient
Solution Approach 1:
The patent implements dynamic storage space planning that automatically adjusts storage space allocation based on real-time warehouse conditions, goods attributes, and predicted future storage needs. The system transitions from static category-based allocation to dynamic optimization, continuously recalculating optimal storage space assignments as goods are added, removed, or change attributes.
Solution Approach 2:
The patent performs preliminary storage space planning by predicting future storage needs based on historical data and current trends. The system proactively reserves and allocates storage spaces before goods arrive, optimizing the layout and assignment in advance rather than reacting to immediate storage requirements.
2Reliability
If goods are dispersed in storage spaces to prevent overflow, then storage capacity is protected, but workload increases and work efficiency decreases
Solution Approach 1:
The patent implements dynamic monitoring and adjustment of storage space utilization, automatically consolidating dispersed goods when storage spaces become underutilized. The system continuously tracks goods distribution and performs intelligent consolidation operations to maintain optimal density while preventing overflow, adapting to changing warehouse conditions in real-time.
Solution Approach 2:
The patent establishes a feedback mechanism that monitors storage space utilization rates, goods attributes, and operation workload. The system uses this feedback to automatically adjust storage space assignments, consolidating goods to optimize density while maintaining capacity constraints, thereby reducing retrieval complexity and improving overall efficiency.
3Ease of operation
If maximum goods storage quantity is specified for storage spaces, then storage limits are controlled, but actual storage capability cannot be fully utilized
Solution Approach 1:
The patent dynamically adjusts storage space capacity parameters based on goods attributes such as size, weight, and shape. Instead of using fixed maximum quantity limits, the system calculates optimal storage capacity for each goods type and adjusts allocation accordingly, allowing storage spaces to be fully utilized while respecting physical constraints and safety limits.
4Ease of operation
If volume or weight limits are imposed on storage spaces, then storage constraints are enforced, but accurate storage space estimation becomes difficult
Solution Approach 1:
The patent employs multiple goods attribute parameters including size, volume, weight, and shape characteristics to accurately estimate storage space requirements. The system dynamically adjusts storage capacity calculations based on the specific attributes of goods being stored, providing precise estimation that accounts for both physical constraints and optimal space utilization.
Solution Approach 2:
The patent implements dynamic recalculation of storage space capacity based on changing goods attributes and warehouse conditions. The system continuously updates storage estimates as goods are added or removed, maintaining accurate real-time information about storage space availability and utilization while enforcing constraints adaptively.
Data Source
AI summary
A method for warehouse storage space planning comprises: obtaining warehouse goods change information of a predetermined time period and current storage space utilization information of a warehouse, wherein the predetermined time period is a future time period; extracting goods identifier and a quantity of goods to be stored within the predetermined time period from the warehouse goods change information of the predetermined time period; determining a storage attribute parameter of the goods to be stored within the predetermined time period based on the goods identifier of the goods to be stored within the predetermined time period; and determining a preset storage space in the warehouse for the goods to be stored within the predetermined time period based on the storage attribute parameter of the goods to be stored within the predetermined time period, the quantity of the to-be-stored goods, and the current storage space utilization information of the warehouse.