using JuMP, EAGO

                     m = Model()

                     EAGO.register_eago_operators!(m)

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

                     @variable(m, -19.58980225336104 <= q <= 16.332536463331582)

                     add_NL_constraint(m, :(log(1 + exp(0.1097699546178803 + 0.5720816873107069*log(1 + exp(-0.26202143930164956 + 0.3006071626990803*$(x[1]) + 0.5737922637127819*$(x[2]) + -0.4709190185724106*$(x[3]))) + 0.11808627755560508*log(1 + exp(0.1103867136686838 + -0.1701144375741399*$(x[1]) + -0.3114105380777681*$(x[2]) + -0.8433602212441*$(x[3]))) + -0.12730937872071246*log(1 + exp(0.7136961022484924 + 0.7290114146079865*$(x[1]) + -0.34482664008964514*$(x[2]) + 0.3719033643881229*$(x[3]))) + 0.6166642606025916*log(1 + exp(0.7095130860135548 + 0.7761479980944426*$(x[1]) + 0.5578694028199163*$(x[2]) + 0.7897154219898308*$(x[3]))) + 0.45996993866072433*log(1 + exp(-0.2424710608654208 + -0.6645249084724911*$(x[1]) + -0.49648246781073047*$(x[2]) + 0.9115115047829443*$(x[3]))))) + log(1 + exp(-0.8288330741680832 + -0.5580861219922526*log(1 + exp(-0.26202143930164956 + 0.3006071626990803*$(x[1]) + 0.5737922637127819*$(x[2]) + -0.4709190185724106*$(x[3]))) + -0.8786358511296881*log(1 + exp(0.1103867136686838 + -0.1701144375741399*$(x[1]) + -0.3114105380777681*$(x[2]) + -0.8433602212441*$(x[3]))) + -0.6915444540383735*log(1 + exp(0.7136961022484924 + 0.7290114146079865*$(x[1]) + -0.34482664008964514*$(x[2]) + 0.3719033643881229*$(x[3]))) + 0.5554450106282389*log(1 + exp(0.7095130860135548 + 0.7761479980944426*$(x[1]) + 0.5578694028199163*$(x[2]) + 0.7897154219898308*$(x[3]))) + -0.20937059223327026*log(1 + exp(-0.2424710608654208 + -0.6645249084724911*$(x[1]) + -0.49648246781073047*$(x[2]) + 0.9115115047829443*$(x[3]))))) + log(1 + exp(0.13615042538554878 + 0.08502572267265318*log(1 + exp(-0.26202143930164956 + 0.3006071626990803*$(x[1]) + 0.5737922637127819*$(x[2]) + -0.4709190185724106*$(x[3]))) + -0.9980047609363689*log(1 + exp(0.1103867136686838 + -0.1701144375741399*$(x[1]) + -0.3114105380777681*$(x[2]) + -0.8433602212441*$(x[3]))) + -0.5678523898140919*log(1 + exp(0.7136961022484924 + 0.7290114146079865*$(x[1]) + -0.34482664008964514*$(x[2]) + 0.3719033643881229*$(x[3]))) + 0.29618367003382495*log(1 + exp(0.7095130860135548 + 0.7761479980944426*$(x[1]) + 0.5578694028199163*$(x[2]) + 0.7897154219898308*$(x[3]))) + -0.7256587322261439*log(1 + exp(-0.2424710608654208 + -0.6645249084724911*$(x[1]) + -0.49648246781073047*$(x[2]) + 0.9115115047829443*$(x[3]))))) + log(1 + exp(-0.16139551949919406 + -0.5886735107938796*log(1 + exp(-0.26202143930164956 + 0.3006071626990803*$(x[1]) + 0.5737922637127819*$(x[2]) + -0.4709190185724106*$(x[3]))) + -0.02630736114123211*log(1 + exp(0.1103867136686838 + -0.1701144375741399*$(x[1]) + -0.3114105380777681*$(x[2]) + -0.8433602212441*$(x[3]))) + -0.03441572289730743*log(1 + exp(0.7136961022484924 + 0.7290114146079865*$(x[1]) + -0.34482664008964514*$(x[2]) + 0.3719033643881229*$(x[3]))) + 0.3935924617025486*log(1 + exp(0.7095130860135548 + 0.7761479980944426*$(x[1]) + 0.5578694028199163*$(x[2]) + 0.7897154219898308*$(x[3]))) + 0.3425056157482871*log(1 + exp(-0.2424710608654208 + -0.6645249084724911*$(x[1]) + -0.49648246781073047*$(x[2]) + 0.9115115047829443*$(x[3]))))) + log(1 + exp(-0.5329713534130147 + -0.3183971019485696*log(1 + exp(-0.26202143930164956 + 0.3006071626990803*$(x[1]) + 0.5737922637127819*$(x[2]) + -0.4709190185724106*$(x[3]))) + 0.5847814320797045*log(1 + exp(0.1103867136686838 + -0.1701144375741399*$(x[1]) + -0.3114105380777681*$(x[2]) + -0.8433602212441*$(x[3]))) + -0.7330877632484647*log(1 + exp(0.7136961022484924 + 0.7290114146079865*$(x[1]) + -0.34482664008964514*$(x[2]) + 0.3719033643881229*$(x[3]))) + -0.37731199331975374*log(1 + exp(0.7095130860135548 + 0.7761479980944426*$(x[1]) + 0.5578694028199163*$(x[2]) + 0.7897154219898308*$(x[3]))) + -0.08817423127621415*log(1 + exp(-0.2424710608654208 + -0.6645249084724911*$(x[1]) + -0.49648246781073047*$(x[2]) + 0.9115115047829443*$(x[3]))))) - $q <= 0.0))

                     @objective(m, Min, q)

                     return m

                    