Evolutionary Computation for Theatre Hall Acoustics

Architectural design is a process that considers many objectives to satisfy. In general, these objectives are conflicting with each other. On the other hand, many design parameters are associated with these conflicting objectives, too. Therefore, architectural design is described as a complex task. To handle the complexity, computational optimization methods can be employed to investigate architectural design process in detail. This paper focuses on investigating Pareto-front solutions for theatre hall design using multi-objective evolutionary algorithms. To formulate the theatre hall acoustic design problem, we consider three objectives. Two objectives are minimization of both reverberation time, and total initial cost whereas the third objective is the maximization of seating capacity. In addition, several designs and acoustical performance constraints are defined. To tackle this problem, a multi-objective self-adaptive differential evolution algorithm (JDEMO) is proposed and compared with a well-known non-dominated sorting genetic algorithm-II (NSGA-II) from the literature. Computational results show that the proposed JDEMO algorithm achieves competitive results when compared to the NSGA-II.