Fig. 4: Performance of qNEHVI-BO and EGBO on MW7 problem. | npj Computational Materials

Fig. 4: Performance of qNEHVI-BO and EGBO on MW7 problem.

From: Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs

Fig. 4

a Optimization trajectory in the decision (left) and objective (right) spaces, obtained for n = 2 variables after 3 runs of 30 iterations with EGBO. b Probability density map in the objective space, obtained for n = 8 variables after 10 runs of 48 iterations with qNEHVI-BO (left) and EGBO (right). The feasible region is highlighted in grey and the infeasible one in red. Low probably density values (blue) indicate sparse sampling in the objective space, while high values (yellow) highlight regions that are intensively sampled. The true unconstrained PF is shown in blue, and the true constrained PF in red. c Evolution of the performance metrics (logΔHV, NU and constraint violations) with the number of iterations for qNEHVI-BO (blue) and EGBO (orange). The HV reference location is indicated by an orange star. We report the mean value of the metric (solid line) as well as its 95% confidence interval across 10 runs (shaded region).

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