System optimization by multiobjective genetic algorithms and analysis of the coupling between variables, constraints and objectives

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

Volumn 24, Issue 3, 2005, Pages 805-820

  Regnier J ^a   Sareni, B ^a   Roboam, X ^a  

^a CNRS   (France)

Author keywords

Electrical engineering; Optimization techniques; Programming and algorithm theory

Indexed keywords

CONSTRAINT THEORY; ELECTRIC INVERTERS; ELECTRIC LOADS; ELECTRIC MOTORS; ELECTRICAL ENGINEERING; GENETIC ALGORITHMS; LARGE SCALE SYSTEMS; PERMANENT MAGNETS; PROGRAMMING THEORY; SENSITIVITY ANALYSIS; SYSTEMS ANALYSIS;

MULTIOBJECTIVE GENETIC ALGORITHMS (MOGA); OPTIMIZATION TECHNIQUES; PERMANENT MAGNET MOTOR; PROGRAMMING AND ALGORITHM THEORY;

OPTIMAL CONTROL SYSTEMS;

EID: 22644443816     PISSN: 03321649     EISSN: None     Source Type: Journal    
DOI: 10.1108/03321640510598157     Document Type: Article

References (12)

1. Coello Coello, C.A. and Lechuga, M.S. (2002), "MOPSO: a proposal for multiple objective particle swarm optimization", Proceedings of the Congress on Evolutionary Computation (CEC2002), IEEE Service Center, Piscataway, NJ, Vol. 2, pp. 1051-6.
2. Corne, D.W., Knowles, J.D. and Oates, M.J. (2000), "The Pareto envelope-based selection algorithm for multiobjective optimization", in Schoenauer, M., Deb, K., Rudolph, G., Yao, X., Lutton, E., Merelo, J.J. and Schwefel, H.P. (Eds), Proceedings of the Parallel Problem Solving from Nature VI Conference, Springer, New York, NY, pp. 839-48.
3. Deb, K., Agrawal, S., Pratab, A. and Meyarivan, T. (2000), "A fast-elitist non-dominated sorting genetic algorithm for multiobjective optimization: NSGA-II", Proceedings of the Parallel Problem Solving from Nature VI Conference, pp. 849-58.
4. Hwang, Ching-Lai and Masud, Abu Syed Md. (1979), Multiple Objective Decision Making - Methods and Applications, Springer, New York, NY.
5. Papoulis, A. and Unnikrishna Pillai, S. (2002), Probability, Random Variables, and Stochastic Processes, 4th ed., McGraw-Hill, New York, NY.
6. Pareto, V. (1896), Cours d'économie politique, Rouge, Lausanne.
7. Régnier, J. (2006), "Conception de systèmes hétérogènes en Génie Electrique par optimisation évolutionnaire multicritère", Thèse de Doctorat, Institut National Polytechnique de Toulouse, Toulouse.
8. Régnier, J., Sareni, B. and Roboam, X. (2003), "Optimal design of electrical engineering systems using Pareto Genetic Algorithms", paper presented at the 10th European Conference on Power Electronics and Applications, Toulouse.
9. Sareni, B., Régnier, J. and Roboam, X. (2004), "Recombination and self-adaptation in multi-objective genetic algorithms", in Liardet, P., et al. (Eds), Lecture Notes in Computer Science, 2936, Springer, New York, NY, pp. 115-26.
10. Slemon, G. and Liu, X. (1992), "Modeling and design optimization of permanent magnet motors", Electrical Machines and Power Systems, Vol. 20, pp. 71-92.
11. Van Veldhuizen, D.A. (1999), "Multiobjective evolutionary algorithms: classifications, analyses, and new innovations", PhD thesis, Department of Electrical and Computer Engineering, Air Force Institute of Technology, Wright-Patterson AFB, OH,.
12. Zitzler, E. (1999), "Evolutionary algorithms for multiobjective optimization: methods and applications", PhD thesis, Swiss Federal Institute of Technology (ETH), Zurich.