Container Stacking Optimization via Priority-Based Simulation
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Solution Overview
Problem
The inefficiency in fetching containers from a storage yard due to random stacking, resulting in a low fetching efficiency as it requires multiple flips to locate the target container.
Innovation Solution
A method and apparatus for container stacking processing that determines a pick-up priority and performs stacking simulations to optimize the stacking state, minimizing the number of flips required to access a container by determining a target stacking state that meets a target flipping condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If containers are randomly stacked in the storage yard, then the stacking process is simple and fast, but the fetching efficiency becomes low due to multiple flips required
Solution Approach 1:
The system performs preliminary stacking simulation and optimization before actual container stacking. By pre-determining the optimal stacking state that minimizes future flips, the system prepares the storage yard configuration in advance, thereby reducing the time required for container acquisition during actual operations.
Solution Approach 2:
The system creates a virtual copy of the storage yard and performs stacking simulations on this digital replica. Multiple stacking schemes are tested in the virtual environment, and the optimal scheme is selected before implementing the actual stacking, avoiding the need for trial-and-error physical operations.
2Productivity
If multiple stacking simulations are performed to optimize stacking state, then the fetching efficiency improves, but the processing complexity increases
Solution Approach 1:
The stacking simulation process is divided into multiple independent stages: determining pick-up priorities, generating candidate stacking schemes, evaluating each scheme, and selecting the optimal configuration. This segmentation allows the complex problem to be solved through a series of simpler, more manageable steps.
Solution Approach 2:
The system changes key parameters such as pick-up priority assignments and stacking positions to generate different candidate schemes. By systematically varying these parameters and evaluating their impact, the system finds the optimal configuration without exhaustively testing all possible arrangements.
3Loss of time
If containers are stacked without considering pick-up priority, then the stacking operation is faster, but the number of flips required increases
Solution Approach 1:
The system uses pick-up priority information as feedback to guide the stacking optimization process. By continuously referencing the pick-up priorities during simulation and evaluation, the system adjusts the stacking configuration to minimize flips for high-priority containers, creating a feedback loop that improves fetching efficiency.
Data Source
AI summary
The present disclosure provides a method and an apparatus for container stacking processing, a device, a storage medium and a product, and relates to the field of data processing. The specific implementation is as follows: determining at least one pick-up priority corresponding to a storage yard, where the pick-up priority is a planned pick-up order set for containers in the storage yard; determining, based on at least one pick-up priority, a target priority respectively corresponding to at least one to-be-stacked container in the storage yard; performing at least one stacking simulation processing on the at least one to-be-stacked container to obtain a stacking state generated from each simulation and obtain at least one stacking state; selecting, from the at least one stacking state, a target stacking state that meets a target flipping condition, according to the target priority respectively corresponding to the at least one to-be-stacked container.