Multi-Objective Drug Molecule Optimization Based on Tanimoto Crowding Distance and Acceptance Probability

. 2025 Aug 20;18(8):1227. doi: 10.3390/ph18081227

Algorithm 1 The framework of the algorithm for NSGA-II.

Require:
P (initial population), N (number of generations)
Ensure:
$P_{f i n a l}$ (pareto front)
1:
$f r o n t s \Leftarrow f r o n t s s o r t i n g (P)$
2:
$c r o w d i n g_d i s t a n c e \Leftarrow c r o w d i n g d i s t a n c e (f r o n t s)$
3:
for $i = 0$ to N do
4:
$P_{i}^{'} \Leftarrow m u t a t i o n (P_{i}) + c r o s s o v e r (P_{i})$
5:
$f r o n t s \Leftarrow f r o n t s s o r t i n g (P_{i}^{'} + P_{i})$
6:
$c r o w d i n g_d i s t a n c e \Leftarrow c r o w d i n g d i s t a n c e (f r o n t s)$
7:
$P_{i + 1} \Leftarrow S e l e c t s a t i s f y c o n d i t i o n s ()$
8:
end for