Optimizing solar access and density in Tel Aviv: Benchmarking multi-objective optimization algorithms

This paper explores the trade-off between redeveloping an urban site with higher density and maintaining solar access for the surrounding context in the hot and dry climate of Tel Aviv. Such trade-offs are important for future urban development in the Middle East, where densification is a demographi...

Full description

Saved in:
Bibliographic Details
Published inJournal of physics. Conference series Vol. 2042; no. 1; pp. 12066 - 12071
Main Authors Wortmann, Thomas, Natanian, Jonathan
Format Journal Article
LanguageEnglish
Published IOP Publishing 01.11.2021
Online AccessGet full text
ISSN1742-6588
1742-6596
1742-6596
DOI10.1088/1742-6596/2042/1/012066

Cover

More Information
Summary:This paper explores the trade-off between redeveloping an urban site with higher density and maintaining solar access for the surrounding context in the hot and dry climate of Tel Aviv. Such trade-offs are important for future urban development in the Middle East, where densification is a demographic and environmental need. We explore this trade-off with multi-objective optimization (MOO). Specifically, we benchmark seven MOO algorithms on two test problems with different, parametric typologies: courtyard and high-rise. For both problems, we aim to maximize Floor Area Ratio and the simulation-based Context Exposure Index, a novel metric based on the Israeli green building code. The high-rise emerges as the better performing typology, and HypE, SPEA2, and RBFMOpt as the most efficient and robust MOO algorithms.
ISSN:1742-6588
1742-6596
1742-6596
DOI:10.1088/1742-6596/2042/1/012066