Multi-Objective Optimization of Dynamic Systems combining Genetic Algorithms and Modelica: Application to Adsorption Air-Conditioning Systems
Uwe Bau, Daniel Neitzke, Franz Lanzerath, André Bardow · Linköping electronic conference proceedings · 2015
The Modelica language enables the fast and convenient development of physical simulation models.These models are often used for simulation studies.The re-use of simulation models for optimizations requires modeladaptions, additional tools or libraries.In this paper, we present a framework to connect Modelica models developed in Dymola to MATLAB's optimization toolbox.As optimization algorithm, we use a multi-objective genetic algorithm.The optimization procedure is tested for an adsorption air-conditioning design.Compared to a full factorial design, the optimization procedure produces better solutions using less evaluations.