Multi-objective Programming And Is Application On The Power Allocation Problem Of Electricity Market

Multi-objective programming is generally no absolute optimal solutions, so how to get its non-inferior solutions is of great importance. Using geometric weighting method proposed a new evaluation function, with this evaluation function can turn the multi-objective programming to the single objective programming, and proved that the solutions obtained on geometric weighting method is non-inferior solutions or weak non-inferior solutions on multi-objective programming. A numerical example to verify the geometric weighting method is feasible.With more attention to the environment today, the power allocation problem of electricity market is no longer a purely economic problem, which is involving the emission of pollutants, the quality of the power and loss of the network, and so on. Therefore it is more reasonable to present the power allocation problem of electricity market to be a multi-objective programming problem. The methods of geometric weighting and max-min method are used to solve the power allocation problem of electricity market, and we can get the robustness of the two methods though average and variance.In the model of power allocation problem of electricity market, under the premises of the consumption of fuel, the emission of pollutants, and no updating of fuel and equipment, there are three methods of reducing the emission of pollutants. The first is formulating a multi-objective programming problem with the emission of pollutants as objective. The second is adding the emission of pollutants with a punish factor to the objective function, which makes the increasing of flue consumption. The last one is give a limitation to the amount of pollution emissions, and take emissions of pollution as constraint.