Algorithm 1. Pseudocode of POA.
Start POA.
1:	Input problem information: variables, objective function, and constraints.
2:	Set POA population size (N) and iterations (T).
3:	Generate the initial population matrix at random using Equation (2). $x_{i,d}\leftarrow l{b}_d+r·(u{b}_d-l{b}_d)$.
4:	Evaluate the objective function.
5:		For $t=1$ to T
6:			For$i=1$ to $N$
7:			Phase 1: Predator attack towards pufferfish (exploration phase).
8:				Determine the candidate pufferfish set for the ith POA member using Equation (4). $C{P}_i\leftarrow \left\{X_{k_i}:F_{k_i}<F_i and k_i\ne i\right\}$.
9:				Select the target pufferfish for the ith POA member at random.
10:				Calculate new position of ith POA member using Equation (5). $x_{i,d}^{P1}\leftarrow x_{i,d}+r·\left(S{P}_{i,d}-I·x_{i,d}\right)$.
11:				Update ith POA member using Equation (6). $X_i\leftarrow \left\{\begin{array}{c}{X}_i^{P1}, F_i^{P1}<F_i;\\ X_i, else.\end{array}\right.$
12:			Phase 2: Defense mechanism of pufferfish against predators (exploitation phase).
13:				Calculate new position of ith POA member using Equation (7). $x_{i,d}^{P2}\leftarrow x_{i,d}+(1-2r)·\frac{\left(u{b}_d-l{b}_d\right)}{t}$.
14:				Update ith POA member using Equation (8). $X_i\leftarrow \left\{\begin{array}{c}{X}_i^{P2}, F_i^{P2}<F_i;\\ X_i, else.\end{array}\right.$
15:			end
16:			Save the best candidate solution so far.
17:		end
18:	Output the best quasi-optimal solution obtained with the POA.
End POA.