Evolutionary computation for architectural design of restaurant layouts
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Date
2015
Authors
Cemre Cubukcuoglu
Ioannis Chatzikonstantinou
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 presents the results obtained by NSGA-II and DE on a restaurant layout optimization problem trying to maximize total profit while minimizing investment. The problem entails the configuration of restaurant functions the decisions regarding the restaurant shell composition (fraction and position of windows dimensions) and how to shape and place the kitchen and service areas. The NSGA-II and DE algorithms are implemented in a Parametric Design Environment that is familiar in the architectural practice. We demonstrate that the DE algorithm achieves slightly better performance in terms of hypervolume calculation and achieve promising results when the Pareto front approximation is examined. To the best of our knowledge this is the first application of multi-objective approach for restaurant design. © 2017 Elsevier B.V. All rights reserved.
Description
Keywords
Architectural Design, Evolutionary Algorithms, Layout Design, Multi-objective Optimization, Parametric Model, Pareto, Approximation Algorithms, Architectural Design, Calculations, Design, Multiobjective Optimization, Optimization, Parameter Estimation, Pareto Principle, De Algorithms, Layout Designs, Layout Optimization, Multi Objective, Parametric Design, Parametric Modeling, Pareto, Total Profits, Evolutionary Algorithms, Approximation algorithms, Architectural design, Calculations, Design, Multiobjective optimization, Optimization, Parameter estimation, Pareto principle, DE algorithms, Layout designs, Layout optimization, Multi objective, Parametric design, Parametric modeling, pareto, Total profits, 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
2279
End Page
2286
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Citations
CrossRef : 3
Scopus : 7
Captures
Mendeley Readers : 22
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