Addressing the high-rise form finding problem by evolutionary computation
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Date
2015
Authors
Berk Ekici
Seckin Kutucu
I. Sevil Sariyildiz
M. Fatih Tasgetiren
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
This paper aims to examine the application of evolutionary algorithms to the form finding problem of high-rise buildings. In the light of mentioned purpose this study concentrates on the conceptual phase of the design process due to the importance of early design decisions. In this respect multiobjective real-parameter constrained optimization is considered as the method of this study in order to solve high-rise design problem. From the point of evolutionary computation we compare two evolutionary algorithms (NSGA-II and DE) focusing on their computational performance and architectural features of the resulting alternatives. Two objective functions are formulated that specifically focus on structural displacement minimization and construction cost per square meter minimization which are clearly conflicting. As a conclusion we discuss in the context of the high-rise design problem the solutions identified by the NSGA-II and DE algorithms. © 2017 Elsevier B.V. All rights reserved.
Description
Keywords
Evolutionary Algorithms, Form Finding, High-rise Building, Multi-objective Optimization, Algorithms, Calculations, Constrained Optimization, Design, Multiobjective Optimization, Optimization, Tall Buildings, Architectural Features, Computational Performance, Construction Costs, Early Design Decisions, Form Finding, High Rise Building, Objective Functions, Structural Displacement, Evolutionary Algorithms, Algorithms, Calculations, Constrained optimization, Design, Multiobjective optimization, Optimization, Tall buildings, Architectural features, Computational performance, Construction costs, Early design decisions, Form finding, High rise building, Objective functions, Structural displacement, Evolutionary algorithms
Fields of Science
0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
7
Source
IEEE Congress on Evolutionary Computation CEC 2015
Volume
Issue
Start Page
2253
End Page
2260
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Citations
CrossRef : 4
Scopus : 8
Captures
Mendeley Readers : 18
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