Intelligent Buffers for Task Selection in Bin Management
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Solution Overview
Problem
In complex managed spaces with numerous storage locations, determining the shortest path between two locations is computationally expensive, and selecting the next task upon completion of a predecessor task can be time-consuming, affecting overall efficiency and increasing carbon footprint.
Innovation Solution
The implementation of intelligent data buffers that store pre-calculated distances and successor lists allows for fast and efficient determination of travel paths and intelligent selection of successor tasks, using a framework that calculates travel distances based on permissible pathways and nodes, and updates these buffers infrequently to minimize overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the shortest path is determined by calculating all possible paths between two locations in a complex managed space, then the path selection accuracy is improved, but the computational time and complexity increase significantly
Solution Approach 1:
The system pre-calculates and stores the shortest path distances between all pairs of locations in a distance matrix before tasks are executed. This preliminary computation allows the system to quickly retrieve pre-computed path information during task execution without performing expensive real-time pathfinding calculations, thus resolving the contradiction between path selection accuracy and computational time.
Solution Approach 2:
The system creates a simplified computational model by copying the managed space layout into a distance matrix that stores pre-computed shortest path distances. This copied representation allows rapid query of path distances without needing to re-calculate paths, maintaining accuracy while reducing computational overhead during operational phases.
2Productivity
If the successor task is selected in real-time upon completion of a predecessor task to minimize time delay, then the operational efficiency is improved, but the complexity of task management increases
Solution Approach 1:
The system pre-calculates and stores successor task lists for each task based on the distance matrix, ranking potential successor tasks by their connecting distance from the predecessor's target location. When a task completes, the system simply retrieves the pre-ranked successor list and selects the next task without performing complex real-time optimization, thus improving operational efficiency while managing complexity through pre-computation.
Solution Approach 2:
The system creates a copied representation of task dependencies and spatial relationships in the form of pre-computed successor lists. This copied structure allows the task management system to make rapid succession decisions by referencing pre-organized task sequences rather than performing complex real-time analysis, balancing responsiveness with computational manageability.
3Measurement precision
If frequent updates of distance calculations are performed to maintain accuracy, then the measurement precision is improved, but the system overhead and computational burden increase
Solution Approach 1:
The distance matrix is computed once during system initialization or when the managed space layout changes, storing stable shortest path distances. This preliminary computation eliminates the need for frequent recalculations, maintaining accuracy for the duration of the managed space configuration while minimizing computational overhead during normal operation. The system only re-computes the distance matrix when structural changes occur in the managed space.
Data Source
AI summary
After receiving a new task which specifies traveling from a first source bin to a first target bin, a computer-implemented method can select a task which specifies traveling from a second source bin to a second target bin, calculate a connecting distance to the new task measured from the second target bin to the first source bin, and compare the connecting distance to the new task with connecting distances to candidate tasks of the selected task. Responsive to determining that the connecting distance to the new task is smaller than the connecting distance to one of the candidate tasks, the method can update a successor list associated with the selected task. Responsive to completion of the selected task, the method can select a successor task from the successor list to execute. The successor task has the shortest connecting distance among the candidate tasks of the selected task.