Benchmarking MATLAB's gamultiobj (NSGA-II) on the Bi-objective BBOB-2016 Test Suite

Anne Auger (1) , Dimo Brockhoff (2) , Nikolaus Hansen (1) , Dejan Tušar (2) , Tea Tušar (2) , Tobias Wagner (3)

1 TAO - Machine Learning and Optimisation
2 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
3 TU - Technische Universität Dortmund [Dortmund]

In this paper, we benchmark a variant of the well-known NSGA-II algorithm of Deb et al. on the biobjective bbob-biobj test suite of the Comparing Continuous Optimizers platform COCO. To this end, we employ the implementation of MATLAB's gamultiobj toolbox with its default settings and a population size of 100.

Mots clés: Benchmarking; Black-box optimization; Bi-objective optimization

Domaines: Réseau de neurones [cs.NE]; Optimisation et contrôle [math.OC]

Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tušar, Tea Tušar, et al.. Benchmarking MATLAB's gamultiobj (NSGA-II) on the Bi-objective BBOB-2016 Test Suite. GECCO 2016 - Genetic and Evolutionary Computation Conference, Jul 2016, Denver, CO, United States. pp.1233-1239, ⟨10.1145/2908961.2931706⟩. ⟨hal-01435445⟩