Study on DNA Storage Encoding Based IAOA under Innovation Constraints

. 2023 Apr 18;45(4):3573–3590. doi: 10.3390/cimb45040233

Algorithm 1. Pseudo-code of the IAOA.

1: Initialization parameters and population location

X

_i (i = 1,2...N)
2: While(t < T)
3:

M O P (t) = (1 - \frac{t^{\frac{1}{α}}}{T^{\frac{1}{α}}}) \times g, M O A (t) = (m i n + (m a x - m i n) \times \frac{t^{1 / 3}}{T^{1 / 3}}) \times h

4: for i = 1 : N
5: for j = 1 : N
6: if r1 > MOA
7: if r2 > 0.5 (exploration phase)
8:

x_{i, j} (t + 1) = w_{1} \times b e s t (x_{j}) \div (M O P + ε) \times V_{j}

9: else
10:

x_{i, j} (t + 1) = w_{2} \times b e s t (x_{j}) \times M O P \times V_{j}

11: end if
12: if r3 > 0.5 (development phase)
13:

{x_{i, j} (t + 1) = w}_{1} \times b e s t (x_{j}) - M O P \times V_{j}

14: else
15:

x_{i, j} (t + 1) = w_{2} \times b e s t (x_{j}) + M O P \times V_{j}

16: end if
17: end if
18: end for
19: end for
20: end while
21: Return to the optimal solution