Title :
Pareto Multi Objective Optimization
Author :
Ngatchou, Patrick ; Zarei, Anahita ; El-Sharkawi, M.A.
Author_Institution :
Washington Univ., Seattle, WA
Abstract :
The goal of this chapter is to give fundamental knowledge on solving multi-objective optimization problems. The focus is on the intelligent metaheuristic approaches (evolutionary algorithms or swarm-based techniques). The focus is on techniques for efficient generation of the Pareto frontier. A general formulation of MO optimization is given in this chapter, the Pareto optimality concepts introduced, and solution approaches with examples of MO problems in the power systems field are given
Keywords :
Pareto optimisation; evolutionary computation; particle swarm optimisation; Pareto optimazation; evolutionary algorithm; intelligent metaheuristic approach; pareto multiobjective optimization; particle swarm optimization; power systems; swarm-based technique; Constraint optimization; Cost function; Delta modulation; Evolutionary computation; Pareto analysis; Pareto optimization; Power engineering and energy; Stability; Systems engineering and theory; Voltage;
Conference_Titel :
Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
1-59975-174-7
DOI :
10.1109/ISAP.2005.1599245
