Gurobi ignores constraints

Okay I have tried to find a problem of small size so I can post it here that also shows this behavior:

A is a sparse complex double 189x35 with values:

 (135,1)     -0.1367 + 0.1749i
 (136,2)      0.3306 - 1.4107i
 (137,3)      0.3082 - 0.9338i
 (138,4)      0.6593 - 0.0817i
 (139,5)      0.8954 + 0.4595i
 (142,6)     -0.0576 + 0.8289i
 (143,7)      0.0082 - 0.9681i
 (144,8)     -0.1282 - 0.7835i
 (145,9)      0.4682 - 0.1218i
 (146,10)     1.1559 + 0.4019i
 (149,11)    -0.5109 + 1.3432i
 (150,12)    -0.8386 - 0.3687i
 (151,13)    -1.1434 - 0.3746i
 (152,14)    -0.4320 + 0.0146i
 (153,15)     0.5149 + 0.3410i
 (156,16)    -1.0249 + 1.5887i
 (157,17)    -1.5286 + 0.0538i
 (158,18)    -1.9509 - 0.0512i
 (159,19)    -1.2376 + 0.1025i
 (160,20)    -0.2473 + 0.2031i
 (163,21)    -0.9040 + 1.6541i
 (164,22)    -1.4053 + 0.1511i
 (165,23)    -1.8340 - 0.0006i
 (166,24)    -1.1514 + 0.0509i
 (167,25)    -0.2053 + 0.0614i
 (170,26)    -0.3075 + 1.4840i
 (171,27)    -0.6141 - 0.0928i
 (172,28)    -0.9139 - 0.2075i
 (173,29)    -0.2691 - 0.0842i
 (174,30)     0.5634 + 0.0011i
 (177,31)    -0.0308 + 0.9085i
 (178,32)     0.0584 - 0.5424i
 (179,33)    -0.0019 - 0.4877i
 (180,34)     0.5524 - 0.1569i
 (181,35)     1.1244 + 0.0683i

b is a complex double 189x1 with the following values

0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.00000000000000 + 0.00000000000000i
0.451767892286248 - 0.0984887685992476i
-0.186746287565961 - 0.234210313521049i
-0.238986677779402 - 0.162931702335663i
-0.108019031983878 - 0.0255370344699410i
0.0624773386874219 + 0.0619360566624633i
-0.0507106034192851 + 0.109103863179097i
-0.127467959301767 + 0.0251467219763494i
0.0666658055458473 - 0.0548227929207385i
-0.0813844508335685 - 0.0218026386120410i
-0.0820679949343032 + 0.0198765786071449i
-0.0112529687722592 + 0.0526438968550827i
0.0836580727468601 + 0.0477425284687704i
0.00355951427924545 + 0.0518731443499330i
-0.0539214938161495 + 0.0187313822942415i
0.163303763602547 - 0.0635323596692992i
-0.113183247016945 - 0.0497037574804551i
-0.115550082696522 + 0.0121551619440631i
-0.0154684578885712 + 0.0683736091289466i
0.100964183042530 + 0.0709684813352773i
-0.0198239474131061 + 0.0746670647141227i
-0.116776030566267 + 0.0190795745477130i
0.167982806160731 - 0.0603182094059083i
-0.124935861747283 - 0.0702828640627505i
-0.130155507106062 - 0.00314970532293843i
-0.0200062601527203 + 0.0662538381398065i
0.0979050572101737 + 0.0764718086854680i
-0.0462833790394791 + 0.0784580936450336i
-0.161777593142035 + 0.00957275068951476i
0.133020624365489 - 0.0449856977253197i
-0.118931365583437 - 0.0804272625178288i
-0.123490805374515 - 0.0179016145774857i
-0.0115195108958254 + 0.0540691772551751i
0.102567193347161 + 0.0678176281886014i
-0.0529340473245425 + 0.0708568638741452i
-0.174726774711446 + 0.000457544296932331i
0.136165454559517 - 0.0195220890769397i
-0.103617154683121 - 0.0803790496728034i
-0.103705808105524 - 0.0238078399416313i
0.00674003168769088 + 0.0436321007599248i
0.117550498822787 + 0.0565574412292208i
-0.0378169689315449 + 0.0624002479131001i
-0.157862691058826 - 0.00272905109715679i
0.152432779665275 - 0.0155656616792726i
-0.0897966417891108 - 0.0680899093187325i
-0.0855489889892977 - 0.0160992478814708i
0.0173778857016314 + 0.0421782192403136i
0.123734857929576 + 0.0508709549566237i
-0.0183957437700206 + 0.0594886200512273i
-0.127720193444215 + 0.00343276839472515i
0.110241821985153 - 0.0460574170483952i
-0.0802186976402323 - 0.0433040937918527i
-0.0762026347110561 + 0.00172357157714947i
0.00617471299674294 + 0.0463020693059800i
0.0969321759717160 + 0.0497130287699387i
-0.0125180752600083 + 0.0588762545132580i
-0.0958746705828264 + 0.0154352779374145i
0.0255874180120349 - 0.0638047518937523i
-0.0648768749025830 - 0.0135118078110220i
-0.0649839174849397 + 0.0174920624416018i
-0.0200996711151028 + 0.0432625707771713i
0.0170560861991252 + 0.0484749127356651i
-0.0196610215316924 + 0.0491359066250268i
-0.0548279397979754 + 0.0184327916292436i

here is the code:

data = load('inputData.mat');
A = data.A;
b = data.b;
p0 = ones(35,1)*0.5;
g = data.g
p_range = g.p_range
cvx_begin
    %cvx_solver mosek %works as expected
    cvx_solver gurobi %constraints not fulfilled
    
    variable dp(length(p0))
    minimize norm(A*dp - b)
    subject to
        p0 + dp <= p_range(:,2)
        p0 + dp >= p_range(:,1)
cvx_end

result = p0 + dp;

p_range(:,2) holds 1s p_range(:,1) holds 0s

this gives me result(1,1) = 1.0952.

If you don’t want to paste the data by hand here is the .mat file: