Research Tools

OPtimizatiOn Solver with SUrrogate Models


OPtimizatiOn Solver with SUrrogate Models

Opossum is an optimization plug-in for Grasshopper and includes two of the best-performing, single-objective optimization algorithms available for the platform: model-based RBFOpt and evolutionary CMA-ES. It also includes the multi-objective RBFMOpt, and the multi-objective MACO (Ant Colony), MOEA/D, NSGA-II and NSPSO (Particle Swarm) algorithms from the Pygmo 2 library.

RBFOpt uses advanced machine learning techniques to find good solutions with a small number of function evaluations, i.e. simulations, while CMA-ES reliably finds near-optimal solutions when many function evaluations are possible. RBFMOpt won the “2-Objective Expensive” track of the international Black Box Optimization Competition 2019, surpassing the winner of the previous two years, the commercial algorithm Artelys Nitro.


ICD: Thomas Wortmann, Zuardin Akbar, Max Zorn
SUTD: Wyton Chu, Peter Jagadprama


title={Opossum - Introducing and Evaluating a Model-based Optimization Tool for Grasshopper},
author={Wortmann, Thomas},
editor = {Janssen, Patrick and Loh, Paul and Raonic, Aleksandra and Schnabel, Marc A.},
booktitle = {Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference},
publisher = {CAADRIA},
venue = {Hong Kong, CN}

Contact Information

This image shows Thomas Wortmann

Thomas Wortmann

Ph.D.,Dipl.-Ing., M.Sc.

Tenure Track Professor | Architectural Computing

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