Abstract:

For the conservative defect of the robust linear optimization model with ellipsoid uncertainty data, a new robust linear optimization formula is proposed. Through introduction of the new distance formula, the ellipsoid uncertainty data are mapped to the unit ball so as to improve the robust linear optimization model. The new model overcomes the conservative defect of the original model when the data perturbations are larger, so the solution of the new model gets a relatively good balance between robustness and optimality. Several standard practical problems are tested; the simulation results show that the new model not only can ensure the robustness of solution but also has good optimality.