Conceptual Airport Terminal Design using Evolutionary Computation
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Date
2015
Authors
Ioannis Chatzikonstantinou
Sevil Sariyildiz
Michael S. Bittermann
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Passenger terminals are very complex buildings not only in their function form and structure but also in infrastructure security comfort energy which deal with huge investments both in terms of capital as well as in terms of resources and environmental impact. As such it is expected that they are designed to fulfill their purpose while minimizing their negative aspects to the environment. Identifying design solutions that satisfy these goals is a challenging task due to the complexity involved. The design task is characterized by excessive number of solutions conflicting goals and complex relations between design decision variables objectives and constraints. As such appropriate informed decisions that integrate as many design aspects as possible should be ensured as early as the conceptual stage of the design. In this study the problem of conceptual airport terminal design is addressed by means of computational decision support methodologies. The proposed method is based on the integration of the following components: i. a parametric modeling approach for enabling the instantaneous generation of a wide variety of designs ii. a multi-faceted evaluation scheme which integrates functional energy and architectural aspects iii. a Multi-Objective Genetic Algorithm namely the NSGA-II to identify well performing solutions. A computational model implementing the method is outlined and validation of the method is performed based on two different scenarios corresponding to commonly occurring airport configurations. The performance of two optimization runs with different population sizes as well as qualitative aspects of the resulting solutions is discussed.
Description
Keywords
evolutionary computation, multi-objective optimization, genetic algorithms, terminal design, architecture, SYSTEM, Evolutionary Computation, Terminal Design, Genetic Algorithms, Multi-Objective Optimization, Architecture, architecture, multi-objective optimization, evolutionary computation, terminal design, genetic algorithms
Fields of Science
0502 economics and business, 05 social sciences, 01 natural sciences, 0105 earth and related environmental sciences
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
5
Source
IEEE Congress on Evolutionary Computation (CEC)
Volume
Issue
Start Page
2245
End Page
2252
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Citations
CrossRef : 1
Scopus : 7
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Mendeley Readers : 30
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