3. Mutation: A bit-wise mutation is applied to the offspring x ′ and y ′ , resulting in new vectors x ′′ , y ′′ . Specifically, a subset of points is randomly selected, and the values at these points are swapped between 0 and 1 to produce the new vectors x ′′ , y ′′ . 4. Survival of the Fittest: For each of x ′′ and y ′′ , the algorithm assesses whether it represents an improvement over the existing solutions in P . Only vectors not dominated by any member of P are retained. Here, we define a solution x dominating another solution x ′ , i.e, x ≻ x ′ if g 1 (x) ≥ g 1 (x ′ ) and g 2 (x) ≥ g 2 (x ′ ) and either g 1 (x) > g 1 (x ′ ) or g 2 (x) > g 2 (x ′ ).