using JuMP, EAGO

                     m = Model()

                     EAGO.register_eago_operators!(m)

                     @variable(m, -1 <= x[i=1:3] <= 1)

                     @variable(m, -19.736879506320445 <= q <= 22.217442927624916)

                     add_NL_constraint(m, :(log(1 + exp(-0.3136061325511519 + 0.2821341474705279*log(1 + exp(0.7833824073251248 + 0.1390648465658577*$(x[1]) + -0.6617731040629309*$(x[2]) + -0.5974574624055107*$(x[3]))) + 0.4396178028948987*log(1 + exp(-0.7125949557702831 + 0.9109805514170546*$(x[1]) + 0.42115237771853087*$(x[2]) + 0.7134573642319126*$(x[3]))) + -0.24849525966922226*log(1 + exp(-0.36270963442709325 + 0.07407412170431016*$(x[1]) + -0.6239570881148437*$(x[2]) + -0.6542866380333012*$(x[3]))) + 0.5972646324288218*log(1 + exp(-0.5451890615285553 + -0.19626106399785304*$(x[1]) + 0.5284606976702149*$(x[2]) + 0.2694706847237054*$(x[3]))) + -0.8620507270647968*log(1 + exp(0.35158020081654806 + 0.8300503955389886*$(x[1]) + -0.8477304064925764*$(x[2]) + 0.1840810006485709*$(x[3]))))) + log(1 + exp(-0.9705953045797062 + -0.6259685253929317*log(1 + exp(0.7833824073251248 + 0.1390648465658577*$(x[1]) + -0.6617731040629309*$(x[2]) + -0.5974574624055107*$(x[3]))) + 0.41918630672941015*log(1 + exp(-0.7125949557702831 + 0.9109805514170546*$(x[1]) + 0.42115237771853087*$(x[2]) + 0.7134573642319126*$(x[3]))) + -0.9388772793667424*log(1 + exp(-0.36270963442709325 + 0.07407412170431016*$(x[1]) + -0.6239570881148437*$(x[2]) + -0.6542866380333012*$(x[3]))) + -0.18849282727638839*log(1 + exp(-0.5451890615285553 + -0.19626106399785304*$(x[1]) + 0.5284606976702149*$(x[2]) + 0.2694706847237054*$(x[3]))) + -0.7819718693068158*log(1 + exp(0.35158020081654806 + 0.8300503955389886*$(x[1]) + -0.8477304064925764*$(x[2]) + 0.1840810006485709*$(x[3]))))) + log(1 + exp(0.8285261526161638 + 0.6863822914423507*log(1 + exp(0.7833824073251248 + 0.1390648465658577*$(x[1]) + -0.6617731040629309*$(x[2]) + -0.5974574624055107*$(x[3]))) + -0.7060930690780838*log(1 + exp(-0.7125949557702831 + 0.9109805514170546*$(x[1]) + 0.42115237771853087*$(x[2]) + 0.7134573642319126*$(x[3]))) + -0.2956343589188948*log(1 + exp(-0.36270963442709325 + 0.07407412170431016*$(x[1]) + -0.6239570881148437*$(x[2]) + -0.6542866380333012*$(x[3]))) + 0.32353098534638214*log(1 + exp(-0.5451890615285553 + -0.19626106399785304*$(x[1]) + 0.5284606976702149*$(x[2]) + 0.2694706847237054*$(x[3]))) + 0.6963022628505415*log(1 + exp(0.35158020081654806 + 0.8300503955389886*$(x[1]) + -0.8477304064925764*$(x[2]) + 0.1840810006485709*$(x[3]))))) + log(1 + exp(-0.2246585184074279 + 0.8591320330102441*log(1 + exp(0.7833824073251248 + 0.1390648465658577*$(x[1]) + -0.6617731040629309*$(x[2]) + -0.5974574624055107*$(x[3]))) + -0.5037522661683527*log(1 + exp(-0.7125949557702831 + 0.9109805514170546*$(x[1]) + 0.42115237771853087*$(x[2]) + 0.7134573642319126*$(x[3]))) + 0.9621050832972355*log(1 + exp(-0.36270963442709325 + 0.07407412170431016*$(x[1]) + -0.6239570881148437*$(x[2]) + -0.6542866380333012*$(x[3]))) + -0.1995700954953512*log(1 + exp(-0.5451890615285553 + -0.19626106399785304*$(x[1]) + 0.5284606976702149*$(x[2]) + 0.2694706847237054*$(x[3]))) + 0.442251462608958*log(1 + exp(0.35158020081654806 + 0.8300503955389886*$(x[1]) + -0.8477304064925764*$(x[2]) + 0.1840810006485709*$(x[3]))))) + log(1 + exp(0.5761249271362421 + -0.042724357144423575*log(1 + exp(0.7833824073251248 + 0.1390648465658577*$(x[1]) + -0.6617731040629309*$(x[2]) + -0.5974574624055107*$(x[3]))) + -0.4537006876708345*log(1 + exp(-0.7125949557702831 + 0.9109805514170546*$(x[1]) + 0.42115237771853087*$(x[2]) + 0.7134573642319126*$(x[3]))) + -0.12519521024691826*log(1 + exp(-0.36270963442709325 + 0.07407412170431016*$(x[1]) + -0.6239570881148437*$(x[2]) + -0.6542866380333012*$(x[3]))) + -0.7426009177864223*log(1 + exp(-0.5451890615285553 + -0.19626106399785304*$(x[1]) + 0.5284606976702149*$(x[2]) + 0.2694706847237054*$(x[3]))) + -0.8758186284143128*log(1 + exp(0.35158020081654806 + 0.8300503955389886*$(x[1]) + -0.8477304064925764*$(x[2]) + 0.1840810006485709*$(x[3]))))) - $q <= 0.0))

                     @objective(m, Min, q)

                     return m

                    