Ultimately, we presented an architectural design problem and compared the tools for testing Optimus in the design domain. For only one function, Galapagos presented slightly better result than Optimus. Experimental results on the benchmark suite showed that Optimus (jEDE) outperforms other optimization tools, namely Galapagos (genetic algorithm), SilverEye (particle swarm optimization), and Opossum (RbfOpt) by finding better results for 19 out of 20 problems. We reported minimum, maximum, average, standard deviations and number of function evaluations of five replications for each function. We made an experiment using standard test problems in the literature and some of the test problems proposed in IEEE CEC 2005. Optimus implements self-adaptive differential evolution algorithm with ensemble of mutation strategies (jEDE). In this paper, we present Optimus, which is a new optimization tool for grasshopper algorithmic modeling in Rhinoceros CAD software. However, there is a little attention on using optimization methods within the computer aided design (CAD) programs. So, any type of evolutionary and swarm algorithms can be used in this field. Most of the architectural design problems are basically real-parameter optimization problems.

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