*Crowding Distance*

Crowding distance is computed in the same manner, as mentioned in [30] (page 15). Crowding distance is computed for each solution using Equation (15).

$$\text{CD}\_{\dot{\jmath}} = \text{CD}\_{\dot{\jmath}} + \frac{f\_m^{j+1} - f\_m^{j-1}}{f\_m^{\max} - f\_m^{\min}} \tag{15}$$

where *j* is a solution in the sorted list, *fm* is the objective function value of *m*th objective, and *f max m* and *f min m* are the population-maximum and population-minimum values of *m*th objective functions.

#### **4. Multi-Objective Jaya Algorithm for SRM Design Optimization**

In the optimization of SRM, the dimensions in Table 1 represent one solution. All of the solutions are stored in the matrix (*X*), as follows:

$$X = \begin{bmatrix} D\_o^1 & D\_o^2 & D\_o^3 & \cdots & D\_o^n \\ L^1 & L^2 & L^3 & \cdots & L^n \\ \vdots & \vdots & \vdots & \vdots & \vdots \\ \beta\_s^1 & \beta\_s^2 & \beta\_s^3 & \cdots & \beta\_s^n \end{bmatrix} \tag{16}$$

where *m* is the number of variables and *n* is the size of population in one generation.
