Paper Conference

Proceedings of Building Simulation 2017: 15th Conference of IBPSA


Developing an Open Python Library for Urban Design Optimisation – Pyliburo

Kian Wee Chen1, Leslie Norford2
1CENSAM, Singapore-MIT Alliance for Research and Technology, Singapore
2Department of Architecture, Massachusetts Institute of Technology, USA

Abstract: Urban design optimisation is a powerful method for the exploration of multiple designs. In performing an urban design optimisation, we need to link and automatically execute multiple domain-specific applications, a technically complicated setup. Current solutions resolve the technical obstacle by embedding the applications within a single Computer-Aided Design (CAD) application to streamline the setup. The solution leverages the CAD application’s modelling workflow and capability to process the urban geometries for analyses. However, this solution is workflow specific; users either do not have access to optimisation algorithms or are restricted to the capabilities provided by a specific CAD application. For optimisation to be accessible to a wider community, we develop an open Python library, Pyliburo, to provide optimisation capability to all design workflows. Pyliburo aims to be easily integrated into a user’s existing design workflow to provide or enhance optimisation capability. To do so, Pyliburo emphasises interoperability, platform independence, ease of use, integration flexibility and extensibility. There are many ways Pyliburo can be integrated into an existing workflow, and we will show a particular workflow in detail as a case study to demonstrate its capability.
Pages: 1266 - 1273