Evolutionary computation for architectural design of restaurant layouts

Loading...
Publication Logo

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
Impulse
Top 10%
Influence
Average
Popularity
Average

Research Projects

Journal Issue

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 Logo
OpenCitations Citation Count
7

Source

IEEE Congress on Evolutionary Computation CEC 2015

Volume

Issue

Start Page

2279

End Page

2286
PlumX Metrics
Citations

CrossRef : 3

Scopus : 7

Captures

Mendeley Readers : 22

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
1.4021

Sustainable Development Goals

SDG data is not available