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Opportunities in Civil Projects with Artificial Intelligence

 Opportunities in Civil Projects with Artificial Intelligence
Author(s): , , ,
Presented at IABSE Congress: Engineering for Sustainable Development, New Delhi, India, 20-22 September 2023, published in , pp. 1207-1215
DOI: 10.2749/newdelhi.2023.1207
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To analyse and compare different production methods, innovative designs and sustainability are essential keys in civil projects. A promising approach is to combine automated design methods supporte...
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Bibliographic Details

Author(s): (Skanska Sweden AB, Gothenburg, Sweden)
(Skanska Sweden AB, Gothenburg, Sweden)
(Chalmers University of Technology, Gothenburg, Sweden)
(Swedish Transport Administration, Gothenburg, Sweden)
Medium: conference paper
Language(s): English
Conference: IABSE Congress: Engineering for Sustainable Development, New Delhi, India, 20-22 September 2023
Published in:
Page(s): 1207-1215 Total no. of pages: 9
Page(s): 1207-1215
Total no. of pages: 9
DOI: 10.2749/newdelhi.2023.1207
Abstract:

To analyse and compare different production methods, innovative designs and sustainability are essential keys in civil projects. A promising approach is to combine automated design methods supported by artificial intelligence (AI). The purpose of this study was to identify and describe knowledge gaps in this field and necessary method development. A series of interviews were performed with experienced personnel from the construction business in order to point out how evaluation of alternatives in today’s tender processes are performed. Furthermore, a literature review was carried out to determine the possibilities with AI. It can be concluded that requirement documents, and information management need to improve. Furthermore, several methods for multi-objective constrained optimization exists today. If this is combined with a set-based parametric design approach, contractors could increase their ability in finding opportunities.

Keywords:
automation digitalization artificial intelligence multi-objective optimization