def Welfare(self, output_list):
# Initiate an instance of Consumer
C = Consumer(self.c, self.g, self.f, self.A, self.B, self.T)
# Generate the utility list of the consumer instance
utility_list = C.Utility(output_list)
'''
An utilitarian welfare function
'''
welfare = -1 * np.sum(utility_list)
return welfare
def Welfare(self,output_list):
# Initiate an instance of Consumer
C = Consumer(self.c,self.g,self.f,self.A,self.B,self.T)
# Generate the utility list of the consumer instance
utility_list = C.Utility(output_list)
# Generate the parameters for the welfare function
# Obtain overall weight for the welfare function
overall_weight = float(1)
# Obtain individual utility weights for each consumer for the welfare function
utility_weights = Loop(self.c)
# Calculate the welfare
# The welfare function is defined as the (sum of U^(2x)) ^ y, where x are individual weights and y is the overall weight
utility_list_square = np.power(np.e,utility_list)
welfare = (np.sum(np.power(utility_list_square , utility_weights)))
# Obtain the negative of the welfare for minimization
neg_welfare = welfare * -1
return neg_welfare
