A MATLAB Toolbox for Surrogate-Assisted Multi-Objective Optimization
Abdullah Al-Dujaili, S. Suresh · 2016
Surrogate modeling has been a powerful ingredient for several algorithms tailored towards computionally-expensive optimization problems. Concerned with solving black-box multi-objective problems given a finite number of function evaluations and inspired by the recent advances in multi-objective algorithms, this paper presents-based on the MATSuMoTo library for single-objective optimization-a surrogate-based optimization toolbox for multi-objective problems. Moreover, in attempt to highlight the strengths and weaknesses of the employed methods, we benchmark the presented toolbox within the Black-box Optimization Benchmarking framework (BBOB 2016).