Polygon Packing Iterative Scaling for High Filling Rates
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Solution Overview
Problem
Existing polygon packing algorithms result in low filling rates due to large gaps in containers, leading to inefficient use of space in computer graphics and related industries.
Innovation Solution
An object processing method that iteratively selects and enlarges objects to fill available spaces in a container, optimizing the packing result by moving and scaling objects to maximize space utilization until no further objects can be moved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a basic sequential packing algorithm is used to place polygons into a container, then the packing process is simple and easy to implement, but the filling rate is low due to large gaps between objects
Solution Approach 1:
The patent applies dynamics by making the packing process iterative and adaptive. Instead of a static sequential placement, the system dynamically adjusts object positions and sizes through multiple passes. Objects are selected, moved, and scaled based on available spaces, with the process repeating until no further improvements can be made. This dynamic optimization transforms the simple sequential algorithm into an intelligent repacking system that significantly increases filling rate while maintaining implementation simplicity.
Solution Approach 2:
The patent changes key parameters during the packing process, specifically the size scale of objects. By allowing objects to be scaled up or down based on the available container space and their relative positions, the system optimizes the filling rate. The size parameter is not fixed but adapts iteratively, enabling objects to fill gaps more effectively while maintaining the overall packing structure.
2Productivity
If objects are placed sequentially according to a fixed rule, then the packing algorithm is efficient and fast, but large gaps remain between objects resulting in poor space utilization
Solution Approach 1:
The patent performs preliminary actions by first conducting a global optimization pass where all objects are repacked based on the complete set of available spaces. This preliminary repacking creates a better initial configuration before any iterative adjustments are made. The preliminary action ensures that objects are positioned and sized optimally from the start, improving both speed and space utilization.
Solution Approach 2:
The patent maintains continuity of useful action through iterative repacking passes. Instead of a single sequential placement, the system continuously performs selection, movement, and scaling operations across multiple iterations. Each pass builds upon the previous one, continuously improving the packing quality without interruption. This continuous optimization ensures maximum space utilization while maintaining computational efficiency.
3Loss of time
If the packing algorithm stops after initial placement, then the computation time is short, but the filling rate remains low with significant gaps
Solution Approach 1:
The patent implements feedback mechanisms that monitor the packing progress and adjust operations accordingly. After each iterative pass, the system evaluates the current packing state, identifies remaining gaps, and selects objects for repacking based on this feedback. The feedback loop continues until convergence, automatically stopping when no further improvements are possible. This feedback-driven approach optimizes filling rate while minimizing unnecessary computation time.
Solution Approach 2:
The packing system performs self-service optimization by automatically detecting available spaces, selecting appropriate objects, and executing repacking operations without external intervention. The algorithm self-evaluates its progress and determines when to stop, eliminating the need for manual control or excessive computation. This self-service approach achieves high filling rates while keeping computation time efficient and predictable.
Data Source
AI summary
An object processing method includes placing a plurality of objects into a container according to an initial packing algorithm to obtain an initial filling result, wherein the objects and the container are two-dimensional polygons. The method further includes determining a first available space in the container based on the initial filling result, and selecting a first object from the plurality of objects based on the first available space. The method further includes moving the first object to the first available space, and enlarging the first object based on the first available space to obtain an enlarged first object. The method further includes iteratively performing the determining the first available space, the selecting the first object, the moving the first object, and the enlarging the first object until no movable object can be selected from the plurality of objects to generate a repacked container.