Algorithm 1: CMA-ES in MOEA/D-HH Framework

Input:$\mathrm{Setting} \mathrm{solution} \mathrm{to} X={B\left(i\right)}^g\cup {\mathrm{A}\left(i\right)}^g$.

Step 1:$\mathrm{Sorting} X$ using the fitness value of the scalarising function.

Step 2:$\mathrm{Updating} \mathrm{distribution} \mathrm{parameters} \mathrm{using} \mathrm{sorted} X$.

Step 3:$\mathrm{Generating} \mathrm{new} \mathrm{solutions}:$

$\hspace{1em} \mathrm{New} \mathrm{solutions} \mathrm{set} Y=Ø. \mathrm{For} i=\mathrm{0,1},\dots ,U_{count}\times \lambda , \mathrm{do}:$

$Y\leftarrow {Y\cup y}_i=m+\sigma \mathrm{C}\frac{z}{\left|\right|z\left|\right|}, \mathrm{where} z~\mathcal{N}(0,\mathrm{I})$.

Step 4:$\mathrm{Repairing}: \mathrm{if} \mathrm{an} \mathrm{element} \mathrm{of} y_i\in Y$ is out of the boundary, its element value is reset to the boundary.

Step 5:$\mathrm{Storing}: {\mathrm{A}\left(i\right)}^{g+1}\leftarrow {\mathrm{A}\left(i\right)}^g\cup Y$

Output: $y_{best}$$, \mathrm{which} \mathrm{is} \mathrm{the} \mathrm{individual} \mathrm{with} \mathrm{best} \mathrm{fitness} \mathrm{value} \mathrm{in} \mathrm{set} Y$.