From: A projection descent method for solving variational inequalities
Dimension of the problem | The method in [ 14 ] | Algorithm 1 with \(\boldsymbol{\alpha ^{*}_{k_{1}}}\) | Algorithm 1 with \(\boldsymbol{\alpha^{*}_{k_{2}}}\) | ||||||
---|---|---|---|---|---|---|---|---|---|
k | l | CPU (sec.) | k | l | CPU (sec.) | k | l | CPU (sec.) | |
n = 100 | 318 | 676 | 0.02 | 157 | 793 | 0.02 | 84 | 298 | 0.06 |
n = 300 | 435 | 995 | 0.06 | 199 | 936 | 0.07 | 164 | 613 | 0.16 |
n = 500 | 489 | 1,035 | 0.14 | 190 | 769 | 0.12 | 155 | 550 | 0.22 |
n = 600 | 406 | 877 | 0.20 | 129 | 402 | 0.08 | 89 | 300 | 0.14 |
n = 800 | 386 | 832 | 0.35 | 169 | 714 | 0.32 | 89 | 309 | 0.26 |