| id |
cf2017_492 |
| authors |
Kocabay, Serkan; Alaçam, Sema |
| year |
2017 |
| title |
Algorithm Driven Design: Comparison of Single-Objective and Multi-Objective Genetic Algorithms in the Context of Housing Design |
| source |
Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 492-508. |
| summary |
This paper aims to present a dynamic multi objective genetic algorithm (MOGA) framework for the purpose of generating 3D mass models in the context of housing design. The proposed MOGA framework contains static and dynamic modules such as regulations, environmental condition analysis as static, behavioral models, designer-specified goals, domain-specific goals based on building types as dynamic modules. Moreover comparison of two algorithmic approaches, implementation of a single and multiple objective
genetic algorithms are compared in terms of variety and usability of the generated design solutions, fitness approximation performances and the speed of the algorithms (running time). In the scope of this study, the potentials andlimitations of the proposed MOGA framework in 3D form generation, its advantages over single objective genetic algorithm are discussed, conducted with a case study. |
| keywords |
Multi-objective, Genetic Algorithm, Housing Design, Mass-model |
| series |
CAAD Futures |
| email |
|
| full text |
 file.pdf (1,448,394 bytes) |
| references |
Content-type: text/plain
|
Beasley, D., Bull, D.R. and Martin, R.R. (1993)
 An Overview of genetic algorithms: Part 1, fundamentals
, University Computing, 15(2), 58-69
|
|
|
|
|
Bentley, P.J. and Wakefield, J.P. (1997)
Conceptual evolutionary design by a genetic algorithm
, Engineering design and automation, 3, 119-132
|
|
|
|
|
Carpo, M. (2011)
Digital Style
, Log, (23), 41-52
|
|
|
|
|
Chatxikonstantinou, I. (2011)
Evolutionary Computation and Parametric Pattern Generation for Airport Terminal Design
, Doctoral dissertation, TU Delft, Delft University of Technology
|
|
|
|
|
Elezkurtaj, T. And Franck, G. (1999)
Genetic Algorithms in Support of Creative Architectural Design
, European Computer Aided Architectural Design and Education,17, Liverpool, 1999. Proceedings... Liverpool, 1999, 645-651
|
|
|
|
|
Fonseca, C.M. and Fleming, P.J. (1993)
Multiobjective genetic algorithms
, IEE Colloquium on `Genetic Algorithms for Control Systems Engineering' (Digest No. 1993/130), 28 May 1993. 1993. London, UK: IEE
|
|
|
|
|
Frazer, J. (1995)
An Evolutionary Architecture
, AA Themes no 7, London, The Architectural Association
|
|
|
|
|
Gallagher, K. and Sambridge, M. (1994)
Genetic algorithms: a powerful tool for large-scale nonlinear optimization problems
, Computers & Geosciences, 20(7-8), 1229-1236
|
|
|
|
|
Goldberg, D.E. and Deb, K. (1991)
A comparative analysis of selection schemes used in genetic algorithms
, Foundations of genetic algorithms, 1, 69-93
|
|
|
|
|
Goldberg, D.E., and Holland, J.H. (1988)
Genetic algorithms and machine learning
, Machine learning, 3(2), 95-99
|
|
|
|
|
Hayes, J.R. (1978)
Cognitive Psychology: Thinking and creating
, Homewood, Ill.: Dorsey Press
|
|
|
|
|
Holland, J.H. (1975)
Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence
, U Michigan Press
|
|
|
|
|
Horn, J., Nafpliotis, N. and Goldberg, D.E. (1994)
A niched Pareto genetic algorithm for multiobjective optimization
, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence, 27-29 June 1994. Orlando, FL, USA: IEEE
|
|
|
|
|
Kim, I.Y. and de Weck, O.L. (2005)
Adaptive weighted-sum method for bi-objective optimization: Pareto front generation
, Structural and multidisciplinary optimization, 2 (2), 149-158
|
|
|
|
|
Knowles, J.D. and Corne, D.W. (2000)
Approximating the nondominated front using the Pareto archived evolution strategy
, Evolutionary Computation 8(2) 149-172
|
|
|
|
|
Kocabay, S. and Alaçam, S. (2017)
A Multi-Objective Genetic Algorithm Framework for Earlier Phases of Architectural Design - A Case Study
, P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 293-302
|
|
|
|
|
Koza, J.R. (1992)
Genetic programming: on the programming of computers by means of natural selection
, (Vol. 1). MIT press
|
|
|
|
|
Lu, H. and Yen, G.G. (2003)
Rank-density-based multiobjective genetic algorithm and benchmark test function study
, IEEE Transactions on Evolutionary Computation 7(4)
|
|
|
|
|
Murata, T. and Ishibuchi, H. (1995)
MOGA: Multi-objective genetic algorithms
, Evolutionary Computation, IEEE International Conference on (Vol. 1, p. 289). IEEE
|
|
|
|
|
Ormerod, T.C. (2005)
Planning and ill-defined problems
, R. Morris and G. Ward (eds.), The cognitive psychology of planning, Psychology Press, Hove and New York, 53-70
|
|
|
|
| last changed |
2017/12/01 14:38 |
|
