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This paper aims to present a mass customization model for interior spaces of mass housing projects to provide solutions that will increase flexibility in accordance with different user needs.

The research project develops a model that generates an expert system that leads to different spatial variations. The expert system is based on the parameters that are determined depending on the findings of the field study done in the selected site. A modular system that allows different configurations is designed, and the expert system has made it possible to achieve a large number of spatial variations by means of a multi-parameter layout design. In the last phase, an interface is developed as a website that presents the spatial variations for each different user according to their response to the online questionnaire.

All the variations with the outputs obtained from the project are presented to the user through a digital interface, which functions as a website. In this sense, the model acts as a mass customization tool that brings together the needs of the inhabitants and provides specific solutions to them with all the outputs obtained from the project. The main objective of the interface is to provide the user with various interior layout alternatives and modular furniture that meet their needs.

The main originality of the research project is the development of a model that consists of different stages that works as a unique mass customization tool. The most significant specialty of the model is the constitution of an expert system in relation to the raw data obtained from the field study. This expert system generates spatial configurations by the help of the design parameters, and these parameters are mainly variables that differentiate the solutions according to the specific requirements of users in the selected site.

This study aims to present a novel Genetic Algorithm-Based Design Model (GABDM) to provide reduced-risk areas, namely, a “safe footprint,” in interior spaces during earthquakes. This study focuses on housing interiors as the space where inhabitants spend most of their daily lives.

The GABDM uses the genetic algorithm as a method, the Nondominated Sorting Genetic Algorithm II algorithm, and the Wallacei X evolutionary optimization engine. The model setup, including inputs, constraints, operations and fitness functions, is presented, as is the algorithmic model’s running procedure. Following the development phase, GABDM is tested with a sample housing interior designed by the authors based on the literature related to earthquake risk in interiors. The implementation section is organized to include two case studies.

The implementation of GABDM resulted in optimal “safe footprint” solutions for both case studies. However, the results show that the fitness functions achieved in Case Study 1 differed from those achieved in Case Study 2. Furthermore, Case Study 2 has generated more successful (higher ranking) “safe footprint” alternatives with its proposed furniture system.

This study presents an original approach to dealing with earthquake risks in the context of interior design, as well as the development of a design model (GABDM) that uses a generative design method to reduce earthquake risks in interior spaces. By introducing the concept of a “safe footprint,” GABDM contributes explicitly to the prevention of earthquake risk. GABDM is adaptable to other architectural typologies that involve footprint and furniture relationships.