Abstract
Domain experts can benefit from optimisation simply by getting better solutions, or by obtaining knowledge about possible trade-offs from a Pareto front. However, just providing a better solution based on objective function values is often not sufficient. It is desirable for domain experts to understand design principles that lead to a better solution concerning different objectives. Such insights will help the domain expert to gain confidence in a solution provided by the optimiser. In this paper, the aim is to learn heuristic rules on building spatial design by data-mining multi-objective optimisation results. From the optimisation data a domain expert can gain new insights that can help engineers in the future; this is termed innovization. Originally used for applications in mechanical engineering, innovization is here applied for the first time for optimisation of building spatial designs with respect to thermal and structural performance.
Original language | English |
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Title of host publication | Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings |
Editors | Carlos A. Coello Coello, Patrick Reed, Kalyanmoy Deb, Erik Goodman, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim |
Publisher | Springer |
Pages | 671-682 |
Number of pages | 12 |
ISBN (Print) | 978-3-030-12597-4 |
DOIs | |
Publication status | Published - 2019 |
Event | Evolutionary Multi-Criterion Optimization, 10th International Conference, (EMO2019) - East Lansing, United States Duration: 10 Mar 2019 → 13 Mar 2019 https://commerce.cashnet.com/cashnetg/selfserve/EditItem.aspx?PC=3824-REG2&ItemCount=1 |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 11411 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Evolutionary Multi-Criterion Optimization, 10th International Conference, (EMO2019) |
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Abbreviated title | EMO2019 |
Country/Territory | United States |
City | East Lansing |
Period | 10/03/19 → 13/03/19 |
Internet address |
Keywords
- Building spatial design
- Data analysis
- Evolutionary algorithms
- Mixed integer optimisation
- Multicriteria optimisation