Component large screen automatic layout optimization method and system based on constraint genetic algorithm

By adopting a component-based automatic layout optimization method for large screens based on constraint genetic algorithms, the problems of low layout efficiency, complex constraint conflicts, and difficulty in multi-objective optimization in component-based large screen assembly are solved, achieving efficient and automated component layout that meets multi-dimensional constraints.

CN120911273APending Publication Date: 2025-11-07NANJING LES CYBERSECURITY & INFORMATION TECH RES INST CO LTD
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Patent Information

Application Number
CN202511023141.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-24
Publication Date
2025-11-07

AI Technical Summary

Technical Problem

Existing technologies suffer from low layout efficiency, complex constraint conflicts, and difficulty in multi-objective optimization in modular large screen assembly. In particular, when the number of components exceeds 50, the time required for manual arrangement increases exponentially, and it is difficult to simultaneously meet the constraints of space, business logic, and specification indicators.

Method used

A component-based automatic layout optimization method for large screens based on constrained genetic algorithms is adopted. By constructing decision variables and constraints, optimization operations are performed using chromosome encoding and genetic operators, including selection, crossover, and mutation operators, to ensure automatic layout under multi-dimensional constraints.

Benefits of technology

It enables automated layout of large-scale components under complex business rules and specification requirements, improves layout efficiency, reduces manual arrangement time, meets constraints of space, business logic and specification requirements, and optimizes component distribution.

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Abstract

The invention provides a modularized large screen automatic layout optimization method and system based on a constraint genetic algorithm. The method comprises the following steps: constructing decision variables and constraint conditions of modularized large screen layout optimization; encoding components in the large modularized screen to obtain different layout schemes corresponding to different chromosomes, and forming an initial layout group; performing optimization operation on each chromosome in the initial layout group by adopting a genetic operator to obtain a secondary layout group; and taking the secondary generation layout group as a new initial layout group, performing optimization operation again until a preset requirement is met, and outputting a final layout scheme. The system is used for implementing the method. The method is suitable for a visual platform in the fields of smart cities, industrial internet of things and the like, and solves the problem of automatic layout of large-scale components on the premise of meeting complex business rules and standard index requirements.
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