[a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2012.

Bibliographic Details
Main Author: Ingram, Joshua (Joshua Wayne)
Other Authors: Terry Knight and Una-May O'Reilly.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2012
Subjects:
Online Access:http://hdl.handle.net/1721.1/72813
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author Ingram, Joshua (Joshua Wayne)
author2 Terry Knight and Una-May O'Reilly.
author_facet Terry Knight and Una-May O'Reilly.
Ingram, Joshua (Joshua Wayne)
author_sort Ingram, Joshua (Joshua Wayne)
collection MIT
description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2012.
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spelling mit-1721.1/728132019-04-10T22:40:53Z [a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm Assorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm Sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm Improving building performance and diversity using a new form of interactive evolutionary algorithm Ingram, Joshua (Joshua Wayne) Terry Knight and Una-May O'Reilly. Massachusetts Institute of Technology. Dept. of Architecture. Massachusetts Institute of Technology. Dept. of Architecture. Architecture. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. [49]). There have been numerous studies demonstrating the use of optimization in architecture, yet it has not been adopted in the field, especially in the early stages of design. As buildings become more complex, the use of optimization in design becomes more relevant. Still, there is a gap between the way architects work and the role optimization plays in the design process. This work presents a new methodology, IDEA (interactive diversity-driven evolutionary algorithm), for designers to engage optimization in the early stages of design. IDEA is designed to work in a manner that is comfortable to the designer and easily integrated into the design process. By focusing on similarities and differences of form, designers sort design options into clusters. The clusters are used to develop a diversity-metric that IDEA uses to generate diverse design options that satisfy the objective. This work demonstrates a novel approach to interaction to better assist in early stages design. by Joshua Ingram. S.M. 2012-09-13T18:53:10Z 2012-09-13T18:53:10Z 2012 2012 Thesis http://hdl.handle.net/1721.1/72813 806322795 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 66 p. application/pdf Massachusetts Institute of Technology
spellingShingle Architecture.
Ingram, Joshua (Joshua Wayne)
[a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm
title [a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm
title_full [a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm
title_fullStr [a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm
title_full_unstemmed [a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm
title_short [a]sorted selection : improving building performance and diversity using a new form of interactive evolutionary algorithm
title_sort a sorted selection improving building performance and diversity using a new form of interactive evolutionary algorithm
topic Architecture.
url http://hdl.handle.net/1721.1/72813
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