Multi-Objective Search in the Early Phase of Architectural Design

This paper discusses a computational approach in the early design phase, with the purpose of exploring the design space for optimal solutions to multiple technical issues without hindering creativity. This the correct moment for the architect to consider as many options as possible, and it is thus a moment in which the architect needs tools to search and inform his de- sign process. The early design phase is analyzed in its relation to complex “wicked” problems, and typological, architectural and cognitive processes related to it. The importance of interac- tivity in the computational approach is proposed

EDT, C80 and G driven auditorium design

Acoustical Indexes as described in ISO3382-11, with their optimal values, are not necessarily positively correlated. Some of them are in fact negatively correlated2. This means that when designers try to shape a room in such a way as to obtain optimal EDT and C80 values for a certain position in the room, they face contrasting objectives. This problem is further complicated by the fact that rooms are designed for multiple listening positions with different distances from the sound source and from reflecting surfaces. The distribution of energy in time and space that is required to obtain optimal acoustical values for all listening positions in a room is a complex problem. Multi-Objective Optimization Algorithms can deal with contrasting design objectives and aid the designer by generating or suggesting a series of solutions that are said to be non-dominated from each other. This set of solutions is called the Pareto front, and can be of valuable information for acoustic consultants and architects early in the design process. This paper presents the use of Multi-Objective Genetic Algorithms (MOGAs) for the design of shoebox auditoriums using the EDT, C80 and G indexes as fitness functions to determine the room's main dimensions