The results of our constrained optimization experiments are shown in Fig. and tabulated in Tab. II. Two metrics of performance: the number of experiments needed to find a single HOIP that satisfies both objectives, and the number of infeasible measurements encountered along the way. Atlas optimizers use geometric and electronic descriptors of the HOIP components to help guide the search (descriptor details are given in SI Sec. S.1.D). Each optimization run is terminated after it . Numerical results of experiments on real-world applications. For the HOIP and drug design (single obj) applications, % explored is the percentage of the optimization domain (± standard error) needed for each strategy to identify the single best candidate choice. For the drug design (multi-obj) application, % explored is the percentage of the optimization domain needed to indentify all Pareto optimal candidates. For all applications, % infeas is the percentage of all measurements that are infeasible. The best performing strategies for each application and performance metric are bolded. Statistical hypothesis testing is conducted using Welch's t-test.