title: Scipy minimize constrained function
body: <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>