title: Constraints do not follow DCP rules in CVXPY
body: <p>I want to solve this problem using CVXPY but I don't know why I get the following error message:</p>
  
  <blockquote>
    <p>DCPError: Problem does not follow DCP rules. </p>
  </blockquote>
  
  <p>I guess my constraints are not DCP. Is there any way to model this in DCP?</p>
  
  <pre><code>n_k = [10000, 20000]
  
  request_rate = [15, 10]
  
  p_k_1 = np.random.rand(n_k[0])
  
  p_k_2 = np.random.rand(n_k[1])
  
  #params
  p_k_param_1 = cvx.Parameter(1, n_k[0], sign="positive")
  p_k_param_1 = np.array(p_k_1)
  p_k_param_2 = cvx.Parameter(1, n_k[1], sign="positive")
  p_k_param_2 = np.array(p_k_2)
  
  request_rate_param = cvx.Parameter(2, sign="positive")
  request_rate_param = np.array(request_rate)
  
  #varibales
  c_k = cvx.Variable(2)
  T_k = cvx.Variable(2)
  
  
  constraints = [ cvx.sum_entries(c_k) &lt;= 10000,
                 c_k &gt;= 0,
                 c_k[0]==cvx.sum_entries(1-cvx.exp(-request_rate_param[0]*T_k[0]*p_k_param_1)),
                 c_k[1]==cvx.sum_entries(1-cvx.exp((-request_rate_param[1]*T_k[1])*p_k_param_2))]
  
  h_k_1 = request_rate_param[0] * cvx.sum_entries((p_k_param_1 * (1-cvx.exp(-request_rate_param[0]*T_k[0]*p_k_param_1))))
  h_k_2 = request_rate_param[1]* cvx.sum_entries(p_k_param_2 * (1-cvx.exp(-request_rate_param[1]*T_k[1]*p_k_param_2)))
  
  
  obj = cvx.Maximize(cvx.log(h_k_1) + cvx.log(h_k_2))
  prob = cvx.Problem(obj, constraints)
  prob.solve(verbose=True)
  </code></pre>