**Step-4: Attack the Prey**

Since in each cycle, the <sup>→</sup> a drops linearly from 2 to 0, therefore, when |A| < 1 is achieved, the prey comes to a standstill in an unchanging position, and the grey wolves attack it.

## **Step-5: Searches for Prey**

If condition |A| > 1 is achieved, grey wolves are compelled to look for the prey. The exploration approach is depicted in this procedure where the wolves wander away from each other in search of prey, then return to attack the prey.

In addition to this, a flowchart to explain the operation of the GWO-based MPPT technique is depicted in Figure 16.

**Figure 16.** GWO-based MPPT technique [52].

4.2.5. Salp Swarm Algorithm (SSA)

SSA was proposed in 2017 and mimics the salps' swarm behavior. Salps are barrelshaped, jellylike zooplankton with jellylike bodies, and they live in the deep, warm waters of the ocean. It moves by swimming with its gelatinous body, which pumps water all the way through it. It moves by constructing a chain formation of one leader, and rest follow in the chain [53]. Figure 17 shows its flowchart.

At first, a candidate solution for the leader is updated and then for the followers with the solutions found for the leaders. Let the entire chain's primary solution be given by Xm,n, where m = 1, 2, 3, ...... ., M and *n* = 1, 2, 3, ...... , *N* represent salp chain size and verdict variable numbers, respectively. The leader's candidate solutions are rationalized by

$$X\_{m,n}^{nrcw} = P\_n + a\_1 \left\{ \left( X\_n^+ - X\_n^- \right) a\_2 + X\_n^- \right\} a\_3 \ge 0.5 \tag{26}$$

$$X\_{m,n}^{new} = P\_n - a\_1 \left\{ \left( X\_n^+ - X\_n^- \right) a\_2 + X\_n^- \right\} a\_3 < 0.5 \tag{27}$$

Random numbers a2 and a3 are distributed evenly between [0, 1], as per the following Equation:

$$a\_1 = 2e^{-(4i/I)^2} \tag{28}$$

where i= current iteration, and I= iterations maximum count.

This solution aids in updating the followers' candidate solutions:

$$X\_{m,n}^{new} = \frac{X\_{m,n} + X\_{m-1,n}}{2} \tag{29}$$

If, after modifying the candidate solutions as recommended in Equations (26), (27), and (29), the entire chain candidate solutions still breach the minimum and maximum standards of verdict variables, the candidate solutions must be reinitialized at the appropriate minimum and maximum values of verdict variables.

**Figure 17.** SSA-based MPPT technique [46].


**Table 3.**

Taxonomy on recent reported work on swarm intelligence

 techniques to track GMPP.


*Mathematics* **2023**, *11*, 269

**Table 3.** *Cont.*



 loss

**Table**

**4.**

*Cont.*

Ali MHM [73]

•

High tracking efficiency

•

Oscillations around GMPP


