Fair premium pricing is one of the main concerns in insurance texts. In this paper, by considering the demand functions, costs of claims and values at risks in homogenous risk groups of cargo insurance policies, we determine the optimum premiums. Higher prices lead to have higher income from policy, meanwhile the number of customers will be reduced. Therefore, optimizing the prices is necessary. In this paper, the estimated demand functions are exponential. Hence, the proposed price optimization problem is nonlinear with a nonlinear constraint. The constrain leads to having higher prices for bad risks and lower prices for good ones. In addition, the proposed model makes it possible to control the average of the values at Risks. Calculations show that for these datasets, the values of elasticities are lower for good risks. Moreover, increasing the average of values at risks reduces the optimum prices and increases the income. Meanwhile, increasing the average of values at risks for higher than special values, does not increase the income.