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

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Publicly Funded

No
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Top 10%
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Average
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Average

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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

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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

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Mendeley Readers : 18

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