Toward a symbiotic coevolutionary approach to architecture
Creative evolutionary systems
A Self-Adaptable Distributed Evolutionary Algorithm to Tackle Space Planning Problems
PARA '02 Proceedings of the 6th International Conference on Applied Parallel Computing Advanced Scientific Computing
Dominant and Recessive Genes in Evolutionary Systems Applied to Spatial Reasoning
AI '97 Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Evolutionary Case-Based Design
AE '99 Selected Papers from the 4th European Conference on Artificial Evolution
Architecture's New Media: Principles, Theories, and Methods of Computer-Aided Design
Architecture's New Media: Principles, Theories, and Methods of Computer-Aided Design
Towards creative design using collaborative interactive genetic algorithms
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
EMO-based architectural room floor planning
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
GENETICA: A computer language that supports general formal expression with evolving data structures
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
The drafting of floor plans is mostly hand made in today's architectural design process. The use of computerized floor planning techniques may enhance the practitioner's range of solutions and expedite the design process. However, despite the research work that has been carried out, the results obtained from these techniques do not convince many practitioners to accept them as part of their design methods. The existing literature shows that every research approach is different in the way in which architectural space planning is tackled. Consequently, each approach tends to be too specific or too abstract. The Space Allocation Problem in architecture may be stated as the process of determining the position and size of several rooms and openings according to the user's specified design program requirements, and topological and geometric constraints in a two-dimensional space. This is the first part of a paper that describes an enhanced hybrid evolutionary computation scheme that couples an Evolutionary Strategy (ES) with a Stochastic Hill Climbing (SHC) technique to generate a set of floor plans to be used in the early design stages of architectural practice. It presents the mathematical model with the problem statement and how the individuals' fitness is computed, the implemented methodological approach, how the adaptive operators are implemented, the summary of the overall procedure, and conclusions.