Downloads
Codes for Surrogate Model Based Optimization
SOCEMO Surrogate Optimization of Computationally Expensive Multi-Objective Problems
This MATLAB implementation uses surrogate model optimization techniques to solve computationally expensive multi-objective black-box optimization problems with box constraints. All optimization parameters have to be continuous.
SOCEMO (MATLAB only) code click to download the zip archive
Journal article: J. Mueller. SOCEMO: Surrogate Optimization of Computationally Expensive Multi-Objective Problems, INFORMS Journal on Computing, 2017, 29(4):581-596
MISO Mixed Integer Surrogate Optimization framework
A MATLAB implementation of a surrogate model algorithm for computationally expensive mixed-integer black-box optimization problems with box constraints. Allows to choose from different radial basis function types, sampling strategies, and initial experimental design options.
MISO (MATLAB only) code click to download the zip archive
Journal article: J. Mueller. MISO: Mixed-Integer Surrogate Optimization framework, Optimization and Engineering, 17(1): 177-203, 2016
MATSuMoTo MATLAB Surrogate Model Toolbox
Surrogate model toolbox for box-constrained global optimization problems (continuous, pure integer, mixed-integer). Contains various surrogate model mixtures, initial experimental design strategies, and sampling strategies
Stochastic RBF codes - implementation based on this paper
Surrogate model optimization algorithm applicable for computationally expensive, black-box global optimization problems. MATLAB version requires MATLAB 2010b or newer. For doing several evaluations in each iteration, MATLAB Parallel Computing Toolbox is required. Python version requires Python 2.7.
DYCORS codes - implementation based on this paper
Surrogate model optimization algorithm applicable for computationally expensive, black-box global optimization problems with large dimensions (>30). MATLAB version requires MATLAB 2010b or newer. For doing several evaluations in each iteration, MATLAB Parallel Computing Toolbox is required. Python version requires Python 2.7.