A design evaluation model for architectural competitions: Measuring entropy of multiple factors in the case of municipality buildings

Various types of information embedded in the built environment or buildings can be measured by using methods such as entropy to give objective, precise and quantitative results. Jury evaluation is a process where buildings are evaluated subjectively without predefined selection criteria, and that criteria are weighted. The model developed in this study investigates the relationship between entropy values calculated for buildings, and the success obtained as a result of the jury evaluation. Since both design and jury evaluation are not dependent on a single factor, the relationship between single entropy values and the success of the proj- ects cannot be questioned. Therefore, the model being developed in this study handles 5 different entropy values calculated according to 5 factors, weighted independently, and finds total entropy values. To achieve similar results to jury evaluation, a non-dominated sorting algorithm for weighting factors was utilized in relation to an inverted U graph. By finding the weighting between the entro- py values, the study aims to resolve a parametric foundation for jury evaluation. Within the scope of this study, 24 municipality building projects designed for architectural project competition between 2015 and 2016 in Turkey, and which have received awards have been evaluated.


Arnheim, R. (1971). Art and Entropy: An Essay on Disorder and Order. Berkeley: University of California Press.

Berlyne, D. E. (1960). Conflict, arousal, and curiosity. New York: Mc- Graw-Hill.

Berlyne, D. E. (1974). The new experimental aesthetics. In D. E. Berlyne (Ed.), Studies in the new experimental aesthetics (pp. 1-25). Washington, DC: Hemisphere.

Bostancı, S. H. (2008). Kent Siluetlerinin Entropi Yaklaşımı ile Değerlendirmesi. (Unpublished doctoral dissertation) Istanbul Technical University Graduate School Of Science, Engineering And Technology, Istanbul.

Crompton, A. (2012). The entropy of LEGO®. Environment and Planning B: Planning and Design, 39(1), 174-182.

Elsheshtawy, Y. (1997). Urban com- plexity: toward the measurement of the physical complexity of street-scapes. Journal of Architectural and Planning Research, 14, 301-316.

Gero, J. S. & Kazakov, V. (2001), En- tropic-based similarity and complexity measures of 2D architectural drawings. In J. S. Gero, B. Tversky and T. Purcell (eds.), Visual and Spatial Reasoning in Design II, Key Centre of Design Com- puting and Cognition, (pp. 147-161). Sydney: University of Sydney.

Glanzer, M. (1958). Curiosity, ex- ploratory drive, and stimulus satiation. Psychological Bulletin, 55(5), 302.

Gunawardena, G. M. W. L., Kubo- ta, Y., & Fukahori, K. (2015). Visual complexity analysis using taxonomic diagrams of figures and backgrounds in Japanese residential streetscapes. Urban Studies Research, 2015(173862), 1–12.

Güzelci, O. Z. (2017). Investigating the role of Entropy in Design Evaluation Process: A Case Study on Municipality Buildings. In G. Çagdaş, M. Özkar, L.F. Gül, E. Gürer (Eds.) Proceeding of 17th International Conference, CAAD Futures 2017: Future Trajectories of Computation in Design (pp.211-224). Turkey: Istanbul Technical University.

Jupp, J., & Gero, J. S. (2006). Visual style: Qualitative and context-depen- dent categorization. AI EDAM, 20(3), 247-266.

Kan, J. W., & Gero, J. S. (2005). Can entropy indicate the richness of idea generation in team designing?. In A. Bhatt (Ed.), CAADRIA’05, Vol. 1 (pp.451-457). New Delhi.

Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological perspective. New York: Cambridge Uni- versity Press.

Klinger, A., & Salingaros, N. A. (2000). A pattern measure. Environment and Planning B: Planning and Design, 27(4), 537-547.

Krampen, M. (1979). Meaning in the urban environment, London: Pion Limited.

Maddox, J. (1990). Complicated measures of complexity. Nature, 344, 705.

Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for pro- cessing information. Psychological Re- view, 63(2), 81-97.

Nasar, J. L. (1987). The effect of sign complexity and coherence on the per- ceived quality of retail scenes. Journal of the American Planning Association, 53(4), 499-509.

Saklofske, D. H. (1975). Aesthetic complexity and exploratory behavior. Perceptual and motor skills, 41(2), 363- 368.

Shannon, C. E. & Weaver, W. (1949) The Mathematical Theory of Commu- nication. University of Illinois Press, Urbana.

Stamps III, A. E. (1998). Complexity of architectural silhouettes: from vague impressions to definite design features. Perceptual and motor skills, 87(3_sup- pl), 1407-1417.

Stamps III, A. E. (1999). Physical de- terminants of preferences for residen- tial facades. Environment and Behav- ior, 31(6), 723-751.

Stamps III, A. E. (2002). Entropy, visual diversity, and preference. The Journal of general psychology, 129(3), 300-320.

Stamps III, A. E. (2003). Advances in visual diversity and entropy. Envi- ronment and Planning B: Planning and Design, 30(3), 449-463.

Stamps III, A. E. (2004). Entropy and visual diversity in the environment. Journal of Architectural and Planning Research, 21(3), 239-256.

Stamps III, A. E. (2012). Commen- tary on the entropy of LEGO®. Envi- ronment and Planning B: Planning and Design, 39(1), 183-187.

Stamps III, A. E. (2014). Designing for Entropy -1 - Creating stimuli with designed amounts of discrete Shan- non information entropy. Retrieved January 1, 2017 from https://www.re- searchgate.net/profile/Arthur_Stamps/ contributions

Vitz, P. C. (1964). Preferences for rates of information presented by se- quences of tones. Journal of Experi- mental Psychology, 68(2), 176-183.

Kaynak Göster