Creating and Improving a Closed Loop: Design Optimization and Knowledge Discovery in Architecture

Abstract

This paper presents computational methods for creating and improving a closed loop of design optimization and knowledge discovery in architecture. It first introduces a design knowledge-assisted optimization improvement method with the technique - offline simulation - to reduce the computing time and improve the efficiency of the design optimization process utilizing architectural domain knowledge. It then describes a new design knowledge discovery system where design knowledge can be discovered from optimization through an automatic data mining approach. The discovered knowledge has the potential to further help improve the efficiency of the optimization method, thus forming a closed loop of improving optimization and knowledge discovery. The demonstration and validation of both methods are presented in the context of a case study with parametric form-finding for a nursing unit design with two design objectives: minimizing the nurses' travel distance and maximizing daylighting performance in patient rooms.

A fast genetic algorithm for solving architectural design optimization problems

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