EMO-based architectural room floor planning

We propose a spatial plan generator based on our spatial planning algorithm and spatial growth rules, combine it with evolutionary multi-objective optimization, apply the system to architectural room floor planning, and evaluate its potential as a support tool for planning. We also introduce a framework for combining the architectural room floor planning support system with an interactive evolutionary computation component that constitute the next step of our research. The system executes two test runs, evolving the generated room floor plans with four and six objectives, respectively, while we monitor the convergence of each of these objectives. The results show that all objectives converged and a great variety of architectural room floor plans was produced. Obtained plans include a variety of unexpected plans for an architect, which implies that this system is useful for not only beginners who need design support but also for architectural professionals.