Analysing optimisation data for multicriteria building spatial design

Koen van der Blom, Sjonnie Boonstra, Herm Hofmeyer, Michael T.M. Emmerich

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)
1 Downloads (Pure)

Uittreksel

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.
Originele taal-2Engels
TitelEvolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings
RedacteurenCarlos A. Coello Coello, Patrick Reed, Kalyanmoy Deb, Erik Goodman, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim
UitgeverijSpringer
Pagina's671-682
Aantal pagina's12
ISBN van geprinte versie978-3-030-12597-4
DOI's
StatusGepubliceerd - 2019
EvenementEvolutionary Multi-Criterion Optimization, 10th International Conference, (EMO2019) - East Lansing, Verenigde Staten van Amerika
Duur: 10 mrt 201913 mrt 2019
https://commerce.cashnet.com/cashnetg/selfserve/EditItem.aspx?PC=3824-REG2&ItemCount=1

Publicatie series

NaamLecture Notes in Computer Science
UitgeverijSpringer
Volume11411
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

CongresEvolutionary Multi-Criterion Optimization, 10th International Conference, (EMO2019)
Verkorte titelEMO2019
LandVerenigde Staten van Amerika
StadEast Lansing
Periode10/03/1913/03/19
Internet adres

Vingerafdruk

Mechanical engineering
Multiobjective optimization
Data mining
Engineers
Hot Temperature

Citeer dit

van der Blom, K., Boonstra, S., Hofmeyer, H., & Emmerich, M. T. M. (2019). Analysing optimisation data for multicriteria building spatial design. In C. A. Coello Coello, P. Reed, K. Deb, E. Goodman, K. Klamroth, K. Miettinen, & S. Mostaghim (editors), Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings (blz. 671-682). (Lecture Notes in Computer Science ; Vol. 11411). Springer. https://doi.org/10.1007/978-3-030-12598-1_53
van der Blom, Koen ; Boonstra, Sjonnie ; Hofmeyer, Herm ; Emmerich, Michael T.M. / Analysing optimisation data for multicriteria building spatial design. Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. redacteur / Carlos A. Coello Coello ; Patrick Reed ; Kalyanmoy Deb ; Erik Goodman ; Kathrin Klamroth ; Kaisa Miettinen ; Sanaz Mostaghim. Springer, 2019. blz. 671-682 (Lecture Notes in Computer Science ).
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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.",
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van der Blom, K, Boonstra, S, Hofmeyer, H & Emmerich, MTM 2019, Analysing optimisation data for multicriteria building spatial design. in CA Coello Coello, P Reed, K Deb, E Goodman, K Klamroth, K Miettinen & S Mostaghim (redactie), Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. Lecture Notes in Computer Science , vol. 11411, Springer, blz. 671-682, Evolutionary Multi-Criterion Optimization, 10th International Conference, (EMO2019), East Lansing, Verenigde Staten van Amerika, 10/03/19. https://doi.org/10.1007/978-3-030-12598-1_53

Analysing optimisation data for multicriteria building spatial design. / van der Blom, Koen; Boonstra, Sjonnie; Hofmeyer, Herm; Emmerich, Michael T.M.

Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. redactie / Carlos A. Coello Coello; Patrick Reed; Kalyanmoy Deb; Erik Goodman; Kathrin Klamroth; Kaisa Miettinen; Sanaz Mostaghim. Springer, 2019. blz. 671-682 (Lecture Notes in Computer Science ; Vol. 11411).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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AB - 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.

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van der Blom K, Boonstra S, Hofmeyer H, Emmerich MTM. Analysing optimisation data for multicriteria building spatial design. In Coello Coello CA, Reed P, Deb K, Goodman E, Klamroth K, Miettinen K, Mostaghim S, redacteurs, Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. Springer. 2019. blz. 671-682. (Lecture Notes in Computer Science ). https://doi.org/10.1007/978-3-030-12598-1_53