Title :
Competitive co-evolutionary algorithm for constrained robust design
Author :
Min Li ; Guimarães, Frederico ; Lowther, David A.
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Abstract :
A competitive co-evolutionary algorithm is proposed to solve constrained robust design problems. The method uses three populations, among which one population evolves the values of the design variables and the other two evolve the values of two uncertainty variables, accounting for the target and feasibility robustness, respectively. An application to the robust design (minimisation of torque ripples) of an interior permanent magnet machine is presented. Through a worst case analysis, the result from the co-evolutionary algorithm is proven to have a more robust performance than that of the non-robust optimisation if manufacturing tolerance is taken into account. The computation time of the co-evolutionary algorithm may be significantly reduced through the use of parallel computing environments.
Keywords :
constraint theory; design engineering; evolutionary computation; permanent magnet motors; power engineering computing; competitive co-evolutionary algorithm; constrained robust design problem; design variables; interior permanent magnet machine; parallel computing; uncertainty variables; worst case analysis;
Journal_Title :
Science, Measurement & Technology, IET
DOI :
10.1049/iet-smt.2014.0204