Evolutionary Computation for Architectural Design of Restaurant Layouts


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.