Designing self-sufficient floating neighborhoods using computational decision support
Loading...

Date
2015
Authors
Ayca Kirimtat
Ioannis Chatzikonstantinou
I. Sevil Sariyildiz
Ayca Tartar
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
Floating settlements which introduce further design complexities over traditional developments have become an alternative for urban development due to climate change and shortage of land. This study aims to develop a floating settlement concept that presents an approach to the design of floating neighborhoods using parametric modelling techniques in combination with Intelligent Decision Support tools and optimization methods. Optimization results of two algorithms namely NSGA-II and DE are compared regarding to objectives. The objectives considered in this study are walkability within the neighborhoods scenic view and cost-effectiveness. Results suggest that DE performs better than NSGA-II in this problem. An application of the method is presented focusing on the design of floating neighborhoods in the project area namely Urla which is a seaside place along the coastline of Izmir Turkey. © 2017 Elsevier B.V. All rights reserved.
Description
Keywords
Computational Decision Support, Evolutionary Algorithms, Floating Neighborhoods, Multi-objective Optimization, Parametric Modelling, Climate Change, Cost Effectiveness, Evolutionary Algorithms, Multiobjective Optimization, Optimization, Urban Growth, Decision Supports, Design Complexity, Floating Neighborhoods, Intelligent Decision Support Tools, Nsga-ii, Optimization Method, Parametric Modelling, Urban Development, Decision Support Systems, Climate change, Cost effectiveness, Evolutionary algorithms, Multiobjective optimization, Optimization, Urban growth, Decision supports, Design complexity, floating neighborhoods, Intelligent decision support tools, NSGA-II, Optimization method, Parametric modelling, Urban development, Decision support systems
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
9
Source
IEEE Congress on Evolutionary Computation CEC 2015
Volume
Issue
Start Page
2261
End Page
2268
Collections
PlumX Metrics
Citations
CrossRef : 7
Scopus : 13
Captures
Mendeley Readers : 13
Google Scholar™


