MULTI-OBJECTIVE OPTIMIZATION ALGORITHMS AND PERFORMANCE TEST FUNCTIONS FOR ENERGY EFFICIENCY : REVIEW

The application of multiobjective optimization is currently receiving growing interest from researchers with various backgrounds. Most research in this area has understandably concentrated on the selection stage, due to the need to integrate vectorial performance measures with the inherently scalar way in which multi objective reward individual performance. In this review, current multiobjective approaches are discussed, ranging from the conventional analytical aggregation of the different objectives into a single function to a number of population-based approaches and the more recent ranking schemes based on the definition of optimality. The sensitivity of different methods to objective scaling and/or possible concavities are considered. From the discussion, directions for future research in multiobjective fitness assignment and earch strategies are identified, including the incorporation of decision making in the selection procedure, fitness sharing, and adaptive representations