Image Center Layout Optimization Method Based on Improved Genetic Algorithm

Authors

Zhijie Li, School of information and control engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;Follow
Haoqi Shi, School of information and control engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;
Changhua Li, School of information and control engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;Follow
Jie Zhang, School of information and control engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;

Abstract

Abstract: Aiming at the layout optimization methods of image center being influenced by the subjective factors and low level of automation, a method of combining systematic layout planning(SLP) with the improved genetic algorithm is proposed. The layout scheme generated by SLP improves the initial population of the genetic algorithm and increases the diversity of the initial population. In order to improve the efficiency of optimization, the improved algorithm updates the crossover probability and mutation probability adaptively according to the evolution stages and the fitness value of the individuals. On the basis of the layout area model and multi-objective optimization mathematical model established for an image center in Xi'an, the improved genetic algorithm is used to in the simulation. The experimental results show that the improved algorithm is faster and more effective than the traditional genetic algorithm or ant colony algorithm. The method can also improve the automation level of image center layout optimization and provide a reasonable reference scheme for the architectural designers.

Recommended Citation

Li, Zhijie; Shi, Haoqi; Li, Changhua; and Zhang, Jie (2022) "Image Center Layout Optimization Method Based on Improved Genetic Algorithm," Journal of System Simulation: Vol. 34: Iss. 6, Article 1.
DOI: 10.16182/j.issn1004731x.joss.20-1043
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss6/1

First Page

1173

Revised Date

2021-04-06

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-1043

Last Page

1184

CLC

TP391.9

Recommended Citation

Zhijie Li, Haoqi Shi, Changhua Li, Jie Zhang. Image Center Layout Optimization Method Based on Improved Genetic Algorithm[J]. Journal of System Simulation, 2022, 34(6): 1173-1184.

Corresponding Author

Changhua Li,lch304502@126.com

DOI

10.16182/j.issn1004731x.joss.20-1043