非线性函数的分段优化不起作用

Question

这是我要实现的功能。Non linear Equation to optimize。我如何退还总费用？ 这是我的代码。

self._z = 1 self._qt_1 = 0 gurobi变量q_m_i_t也已创建，并且可以单独正常工作。

def __f(self,u):  ## non linear function
    """
    Equation for Deployment cost
    Returns:
        Piecewise Deployment cost
    """
    return ((((u + self._z)*(np.log((u + self._z)/(self._qt_1 +self._z))))+ self._qt_1) - u)

def __deploymentcost_of_vnf(self):  # VNF Deployment cost
    """
    Calculates deployment cost of VNF which is the sum over product of
    dost of deploying an instance of VNF in DataCenter and number of new
    instances
    Returns:
        Deployment cost
    """
    ptu = []
    ptf = []
    npts = 5
    sigma = dict()
    Deploymentcost = 0
    gen10 = itertools.product(self._timeperiod,self._numberOfVNFs,
                              self._datacenters)
    for t, m, i in gen10:
        k = "q_" + str(m) + "_" + str(i) + "_" + str(t)
        self.Vars[k] = self.model.getVarByName(
                        "q_" + str(m) + "_" + str(i) + "_" + str(t))
        u = self.Vars[k]

        sigma["sig_" + str(m) + "_" + str(i)] = 0.2
        sigma1 = sigma["sig_" + str(m) + "_" + str(i)]
        a = sigma1/self._n
        piecewise = 0
        for coo in range(npts):
            ptu.append(0.25 * coo)
            ptf.append(self.__f(ptu[coo]))
        self.model.setPWLObj(u , ptu, ptf)
            #piecewise = piecewise + ptf[coo]
            #overall = piecewise*a  # Scalling regularized answer
            #Deploymentcost = Deploymentcost + overall

            #print Deploymentcost
    return Deploymentcost