How to code max(a, 0) as objective function in cvx

how to code max(a, 0) as objective function in cvx

Presuming you want to minimize it, you can use max(a,0)

help cvx/max
Disciplined convex/geometric programming information:
max is convex, log-log-convex, and nondecreasing in its first
two arguments. Thus when used in disciplined convex programs,
both arguments must be convex (or affine). In disciplined
geometric programs, both arguments must be log-convex/affine.

cvx_begin
variable a
minimize(max(a,0))
a>=-2
cvx_end

Calling SDPT3 4.0: 2 variables, 1 equality constraints

num. of constraints = 1
dim. of linear var = 2


SDPT3: Infeasible path-following algorithms


version predcorr gam expon scale_data
NT 1 0.000 1 0
it pstep dstep pinfeas dinfeas gap prim-obj dual-obj cputime

0|0.000|0.000|6.7e-01|6.7e+00|2.0e+02| 1.000000e+01 0.000000e+00| 0:0:00| chol 1 1
1|1.000|1.000|9.3e-08|7.1e-02|1.1e+01| 7.950084e+00 -7.599994e-01| 0:0:00| chol 1 1
2|0.941|1.000|9.0e-08|7.1e-03|7.0e-01| 7.950084e-02 -6.034994e-01| 0:0:00| chol 1 1
3|1.000|0.951|2.8e-08|1.0e-03|3.8e-02| 1.515619e-02 -1.974860e-02| 0:0:00| chol 1 1
4|0.988|0.988|8.3e-09|8.2e-05|4.6e-04| 1.827344e-04 -4.050789e-05| 0:0:00| chol 1 1
5|0.989|0.989|1.5e-10|7.9e-06|5.0e-06| 2.008423e-06 1.933464e-05| 0:0:00| chol 1 1
6|0.989|0.989|8.3e-12|8.7e-08|5.5e-08| 2.207041e-08 2.124340e-07| 0:0:00| chol 1 1
7|1.000|0.998|5.6e-14|1.6e-10|6.7e-10| 3.031304e-10 8.998885e-11| 0:0:00|
stop: max(relative gap, infeasibilities) < 1.49e-08

number of iterations = 7
primal objective value = 3.03130444e-10
dual objective value = 8.99888493e-11
gap := trace(XZ) = 6.72e-10
relative gap = 6.72e-10
actual relative gap = 2.13e-10
rel. primal infeas (scaled problem) = 5.63e-14
rel. dual " " " = 1.62e-10
rel. primal infeas (unscaled problem) = 0.00e+00
rel. dual " " " = 0.00e+00
norm(X), norm(y), norm(Z) = 2.0e+00, 4.5e-11, 1.0e+00
norm(A), norm(b), normĀ© = 2.4e+00, 3.0e+00, 2.0e+00
Total CPU time (secs) = 0.10
CPU time per iteration = 0.01
termination code = 0
DIMACS: 5.6e-14 0.0e+00 1.6e-10 0.0e+00 2.1e-10 6.7e-10


Status: Solved
Optimal value (cvx_optval): +3.0313e-10

disp(a)
3.0313e-10