Using MOPSO for Optimizing Randomized Response Schemes in Privacy Computing

Table 2

Parameters of our algorithm.

Notation	Value
Population size	100
Repository size	200
Mutation archive size	200
Maximum number of iterations	200
Mutation percentage p	1/3
Initial weight	0.4
Cognitive coefficients c1, c2	2
Number of grids in REP	20
hypercube_limits in REP will change dynamically as with boundaries of particles.