Pareto Multi Objective Optimization

Author

Ngatchou, Patrick ; Zarei, Anahita ; El-Sharkawi, M.A.

Author_Institution

Washington Univ., Seattle, WA

fYear

2005

fDate

6-10 Nov. 2005

Firstpage

84

Lastpage

91

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISAP.2005.1599245

Filename

1599245