Scipy minimize constrained function
<p>I am solving the following optimization problem:</p>

<p><a href="https://i.stack.imgur.com/izgIE.png" rel="noreferrer"><img src="https://i.stack.imgur.com/izgIE.png" alt="enter image description here"></a></p>

<p>with this Python code:</p>

<pre><code>from scipy.optimize import minimize
import math

def f(x):
    return math.log(x[0]**2 + 1) + x[1]**4 + x[0]*x[2]

x0 = [0, 0, 0]

cons=({'type': 'ineq',
       'fun': lambda x: x[0]**3 - x[1]**2 - 1},
      {'type': 'ineq',
       'fun': lambda x: x[0]},
      {'type': 'ineq',
       'fun': lambda x: x[2]})

res = minimize(f, x0, constraints=cons)
print res
</code></pre>

<p>I am getting an error</p>

<blockquote>
  <p>message: 'Inequality constraints incompatible'</p>
</blockquote>

<p>What can cause this error?</p>