Algorithm 1: MOWOA

1: Initialize the whale’s population and set it as Ppopulation

2: Hpopulation ← [], set size of Hpopulation as capacity  // Hpopulation represents the external archives

3: While t < maximum number of iterations do

4:  Normalize the boundary values when search agents are out of the preset bound value

5:   $$(\mathrm{Hpopulation}, \overrightarrow{P_{\ast }^t}) = \mathrm{ND}-\mathrm{C}\_\mathrm{sort}(\mathrm{Hpopulation}, \mathrm{Ppopulation}, \mathrm{capacity})$$

6:  For each search agent do

7:     $$\mathrm{Update} \overrightarrow{a}, \overrightarrow{A}, \overrightarrow{C}, l \mathrm{and} w$$

8:     $$\mathbf{If} w<0.5 \mathbf{and} \left|\overrightarrow{A}\right|\le 1 \mathbf{then}$$

9:      Update the position of the current search agent by using (10)

10:     $$\mathbf{Else\; if} w<0.5 \mathbf{and} \left|\overrightarrow{A}\right|>1 \mathbf{then}$$

11:      Select a random search agent (Xrand)

12:      Update the position of the current search agent by using (13)

13:    Else if w ≥ 0.5 then

14:      Update the position of the current search by using (11)

15:    End if

16:  End for

17:  t = t + 1

18: End while

19: Return Hpopulation