where λ is a mixing parameter ranging from 0.0 to 1.0. This combined score (ξ λ j,t ) is used in place of s j to evaluate the node selection policy in Section 3. The TS policy, which demonstrated a constantly good performance in the Passerini and Strecker reactions, is utilized to investigate different λ values. For each λ value, the ngoal and the mean kinetics score of the goal (denoted as skin goal shortly), that is, an average of s kin j,t , where j is the goal node, are evaluated over 10,000 cycles. The results obtained using the Passerini and Strecker reaction datasets are shown in Figures suggesting that λ ∼ 0.85 may be an optimal value. However, because the dependence on λ cannot be predicted in practical applications, addressing the challenge for robustly handling both metrics in multi-objective optimization remains an open issue for future work.