The purpose of self-evaluation of interior space layout is to assess and reflect on the layout and functionality of the interior space you have designed or arranged. Through self-evaluation, it is possible to find out whether the interior layout meets the needs and objectives of the design expectations and to identify any existing problems or opportunities for improvement. Based on this, in order to adapt to the fuzzy and polymorphic characteristics of the self-evaluation indexes of the indoor space layout of small flats, and to overcome the lack of scientificity and objectivity in the evaluation, this paper, on the basis of analyzing the utilization rate of the indoor effective activity space in small flats, adopts the multi-objective genetic algorithm to solve the problem of optimization of the indoor space layout of small flats and establishes the mathematical model using the example of a 17-square-meter small flat, and makes use of the improved genetic algorithm is used to optimize the indoor space layout. The results show that the multi-objective genetic algorithm can effectively solve the indoor space layout problem of small flats.
 Hare K. Design of living spaces in small space. Procedia-Social and Behavioral Sciences, 2013, 92(10):445-451.
 Iman K, Brenda V. Shared student residential space: a post occupancy evaluation. Journal of Facilities management, 2002, pp. 331-336.
 Mohammad A H. On the performance evaluation of sustainable student housing facilities. Journal of facilities management, 2008, pp. 332-338.
 Lin Daofa, Zhu Xiaoyong, Lan Ying. Discussion on the optimization design of college dormitory space. Furniture and Interior Decoration, 2014, (2): 85-87.
 Liu Sisi. Research on the optimization design of postgraduate dormitory space. Shanxi Architecture, 2007, 33 (20): 20-21.
 Zheng Ying, Zhang Xiaoqin. Research on the optimal design of the box unit space of university dormitory. Sichuan Architecture, 2010, 30 (5): 61-63.
 Hao Yu. Research on the spatial layout of middle school students' dormitories based on POE theory: taking the central part of Inner Mongolia as an example [D]. Hohhot: Inner Mongolia University of Technology, 2018.
 Yingni Zhai, Yi Wang, Yanqiu Huang, Meng Xiaojing. A Multi-objective Optimization Methodology for Window Design Considering Energy Consumption, Thermal Environment and Visual Performance. Renewable Energy, 2019.
 Kanak Kalita, Tanmoy Mukhopadhyay, Partha Dey, Salil Haldar. Genetic Programming-assisted Multi-scale Optimization for Multi-objective Dynamic Performance of Laminated Composites: The Advantage of More Elementary-level Analyses. Neural Computing and Applications, 2019.
 Shelza Suri; Ritu Vijay. A Pareto-optimal Evolutionary Approach of Image Encryption Using Coupled Map Lattice and DNA. Neural Computing and Applications, 2019.
How to cite this paper
Indoor Space Layout Optimization Method Based on Multi-objective Genetic Algorithm
How to cite this paper: Peizhi Han. (2023) Indoor Space Layout Optimization Method Based on Multi-objective Genetic Algorithm. Advances in Computer and Communication, 4(4), 252-259.