Weight pattern evaluation for multiobjective hydrothermal generation scheduling using hybrid search technique
Best weight pattern evaluation is applied for multi-objective hydrothermal scheduling. Weights are computed by statistical measures. Statistical measures characterize the correlation coefficients matrix evolution. The solution methodology hybridizes global and local search techniques. Predator-prey optimization as global and Powells pattern as local technique is taken.
hydrothermal generation scheduling multi-objective predator-prey optimization powells pattern search weighting method