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Multiobjective Design Optimization of Building Space Layout, Energy, and Daylighting Performance
Date
2017-09-01
Author
Gürsel Dino, İpek
Üçoluk, Göktürk
Metadata
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This work is licensed under a
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<p><div class="NLM_sec NLM_sec_level_1" style="box-sizing: border-box; overflow: visible; color: rgb(51, 51, 51); font-family: "Roboto Slab", serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-style: initial; text-decoration-color: initial;"></div></p><div class="NLM_sec NLM_sec_level_1 hlFld-Abstract" style="box-sizing: border-box; overflow: visible; color: rgb(51, 51, 51); font-family: "Roboto Slab", serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-style: initial; text-decoration-color: initial;"><p style="box-sizing: border-box; font-weight: normal;">Computational tools for early architectural design need to address issues related to building performance and integrally consider early design decisions regarding building form, spatial layout, orientation, and envelope articulation. This paper presents (1) a design optimization tool, Multiobjective Architectural Design Explorer (MADE) that supports performative-based building design, and (2) a design exploration strategy that effectively operationalizes MADE for Pareto-based comparative search. MADE implements genetic optimization in two steps. It first generates building layouts that satisfy formal, topological, and placement constraints with a single-objective genetic algorithm. Then, MADE determines the opening sizes of the generated layout(s) by optimizing the buildings’ energy and daylighting performance with a multiobjective genetic algorithm. MADE is tested on the design of a library building and the proposed Pareto-based exploration strategy is demonstrated in the selection of an optimal design. The results point out the feasibility of the presented tool and the design strategy, and that multiple objectives can be satisfied by sequentially optimizing design objectives.</p></div>
Subject Keywords
Civil and Structural Engineering
,
Computer Science Applications
URI
https://hdl.handle.net/11511/46947
Journal
Journal of Computing in Civil Engineering
DOI
https://doi.org/10.1061/(asce)cp.1943-5487.0000669
Collections
Department of Architecture, Article