Sustainability-driven structural design using artificial intelligence
Paper i proceeding, 2019

The construction industry is responsible for a large share of the global environmental impact. The need for addressing sustainability and increased competition calls for the development of innovative design methods that include sustainability in a transparent way. The aim of this work is to propose a framework to use machine learning and artificial intelligence (AI) for structural design optimization based on sustainability and buildability criteria. AI opens up new possibilities to optimize and assess structures early in the planning and design stages. In that way, it is possible to decrease the negative and enhance the positive environmental, economic and social impacts and create a more time‐ and cost‐effective design process. The work is meant to serve as a first step toward the development of AI‐based methods in the construction industry, which can bring digitalization in the construction industry to a new level and create new services and business models.

artificial intelligence

life cycle sustainability assessment

set‐based design


structural design optimization


multi‐criteria decision analysis


Alexandre Mathern

Chalmers, Arkitektur och samhällsbyggnadsteknik, Konstruktionsteknik

Kristine Ek

Chalmers, Arkitektur och samhällsbyggnadsteknik, Konstruktionsteknik

Rasmus Rempling

Chalmers, Arkitektur och samhällsbyggnadsteknik, Konstruktionsteknik

20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report

1058-1065 16517
978-3-85748-165-9 (ISBN)

IABSE Congress New York City 2019 - The Evolving Metropolis
New York City, USA,

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Hållbar utveckling



Building Futures (2010-2018)




Tvärvetenskapliga studier




Miljöanalys och bygginformationsteknik

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