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

Jérémi Regnier (1) , Bruno Sareni (1) , Xavier Roboam (1)

1 LEEI - Laboratoire électrotechnique et électronique industrielle

This paper presents a methodology based on Multiobjective Genetic Algorithms (MOGA’s) for the design of electrical engineering systems. MOGA’s allow to optimize multiple heterogeneous criteria in complex systems, but also simplify couplings and sensitivity analysis by determining the evolution of design variables along the Pareto-optimal front. A rather simplified case study dealing with the optimal dimensioning of an inverter – permanent magnet motor – reducer – load association is carried out to demonstrate the interest of the approach.

Mots clés: System Design; Multiobjective Optimization; Genetic Algorithms; Coupling Analysis

Domaines: Energie électrique

Jérémi Regnier, Bruno Sareni, Xavier Roboam. 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, 2005, vol. 24, pp.805-820. ⟨10.1108/03321640510598157⟩. ⟨hal-00779389⟩