Sustainability is related with environmental, social and economic variables. Each one of these areas is, by itself, complex due to the huge number of factors that one must analyze. Because of the combination of the levels with the factors, and the needed replications, an exponential growth in the number of executions appears. In this paper we describe a methodology that helps us to deal with this complexity applying three key concepts, formal representation of simulation models, optimization algorithms and high-performance computing. We present an infrastructure named NECADA that supports the methodology. This approach can be applied to a building refurbishment or to define optimal parameters in new buildings. The specialists work with the conceptual model, and from it with the system; following the method, they will be able to find optimal scenarios using a selection of build-in heuristics that can be applied for the problem resolution.

Peer Reviewed