Multi-disciplinary and multi-objective optimization problem re-formulation in computational design exploration: A case of conceptual sports building design

Ding Yang, Shibo Ren, Michela Turrin, Sevil Sariyildiz, Yimin Sun

Research output: Contribution to journalArticleScientificpeer-review

32 Citations (Scopus)
32 Downloads (Pure)


The benefits of applying multi-objective optimization (MOO) in building design have been increasingly recognized in recent decades. The existing or traditional computational design optimization (CDO) approaches mostly focus on optimization problem solving (OPS), as they often conduct optimizations directly by assuming the optimization problems in question are good enough. In contrast, the computational design exploration (CDE) approaches defined in this research mainly focus on optimization problem formulation (OPF), which are considered more essential and aim to achieve or ensure appropriate optimization problems before conducting optimizations. However, the application of the CDE is very limited especially in conceptual architectural design. The necessity of re-formulating original optimization problems and its potential impacts on optimization results are often overlooked or not emphasized enough. This paper proposes a new CDE approach that highlights the knowledge-supported re-formulation of a changeable initial optimization problem. It improves upon the traditional CDO approach by introducing a changeable initial OPF and inserting a CDE module. The changeable initial OPF allows expanding the dimensionality of an objective space and design space being investigated, and the CDE module can re-formulate the changeable optimization problem using the information and knowledge extracted from statistical analyses. To facilitate designers in achieving the proposed approach, an improved computational platform is used which combines parametric modeling software (including simulation plug-ins) and design optimization software. Assisted by the platform, the proposed approach is applied to the conceptual design of an indoor sports building that considers multi-disciplinary performance criteria (including architecture-, climate- and structure-related criteria) and a wide range of geometric variations. Through the case study, this paper demonstrates the use of the proposed approach, verifies its benefits over the traditional method, and unveils the factors that may affect the behaviour of the proposed approach. Besides, it also shows the suitability of the computational platform used.

Original languageEnglish
Pages (from-to)242-269
JournalAutomation in Construction
Publication statusPublished - 2018

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Architectural performance
  • Climate performance
  • Computational design exploration
  • Knowledge extraction
  • Multi-disciplinary optimization
  • Multi-objective optimization
  • Optimization problem re-formulation
  • Sports buildings
  • Statistical analysis techniques
  • Structural performance


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