Design of Rectangular Façade Modules through Computational Intelligence

None, None; None, None; None, None; None, None; None, None

Design of Rectangular Façade Modules through Computational Intelligence

Case of Common Space in Healthcare Building

Conference Paper (2017)

Author(s)

Selim Karaman (Yasar University)

Berk Ekici (TU Delft - Design Informatics)

Cemre Çubukçuoglu (Yasar University)

Basak Kundakci Koyunbaba (Yasar University)

Ilker Kahraman (Yasar University)

Research Group

Design Informatics

Multi-objective optimization Evolutionary computation Differential evolution Façade design Healthcare building

DOI related publication

https://doi.org/10.1109/CEC.2017.7969420 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:009da7de-f2e6-43ed-873f-19b67d7aea88

More Info

expand_more

Publication Year

2017

Language

English

Research Group

Design Informatics

Pages (from-to)

1021-1028

ISBN (print)

978-1-5090-4601-0

Event

IEEE Congress on Evolutionary Computation 2017 (2017-06-05 - 2017-06-08), Donostia/San Sebastian, Spain

Downloads counter

177

Abstract

This paper presents an implementation of multi-objective optimization for a rectangular façade design proposal in a healthcare building’s common space. Objectives are to maximize daylight performance and to minimize façade construction cost. The aim of this study is to enhance indoor comfort of an existing healthcare building by concerning cost-effective façade design alternatives subject to several constraints. To handle the problem, we formulate a multi-objective real-parameter constraint problem. In order to solve this, Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Self-Adaptive Ensemble Differential Evolution (jE_DEMO) algorithms are used. Finally, both algorithms are capable to discover desirable set of design alternatives.