title: scipy.optimize.minimize multivariate
body: <p>Im trying to minimize the following function:</p>
  
  <pre><code>def func(x, *args):
    #""" Objective function """
         return ((2*math.pi*2000*((x[0]/2)**2))+(2**(x[0]/2)*(x[1])*1000))
  </code></pre>
  
  <p>with the constraints, bounds and initial values of:</p>
  
  <pre><code> guess=[4,5]
   d1=3
   d2=10 
   h1=3
   h2=10
   v=50
   cons = ({'type': 'ineq','fun' : lambda x: math.pi*x[1]*((x[0]/2)**2)-v})
   bnds = ((d1, d2), (h1, h2))
  </code></pre>
  
  <p>and the optimization fun:</p>
  
  <pre><code>scipy.optimize.minimize(func,guess, method='SLSQP',bounds=bnds, 
  constraints=cons)
  </code></pre>
  
  <p>but i keep getting no solution:</p>
  
  <pre><code>fun: 48281.04745868263
  jac: array([ 25783.35449219,   2828.42675781])
  message: 'Positive directional derivative for linesearch'
  nfev: 12
  nit: 7
  njev: 3
  status: 8
  success: False
  x: array([ 3.        ,  7.07344142])
  </code></pre>
  
  <p>please help me.</p>