Multiple-objective optimization decision-making method for large scale systems

In this paper, the global optimization problem for separable non-convex large-scale systems is considered. A three-level hierarchical optimization algorithm is proposed. It converts the original problem into a separable multi-objective optimization problem. The non-inferior frontier is then convexified and the global optimal solution of the original problem is selected from the set of non-inferior solutions of the multi-objective optimization problem. The theoretical basis of the algorithm is established. Simulation shows that the algorithm is effective.