Title :
A novel adaptive genetic algorithm applied to optimizing linear induction machines
Author :
Zhuang, Y.C. ; Yu, H.T. ; Hu, M.Q. ; Xia, Jun
Author_Institution :
Dept. of Electr. Eng., Southeast Univ., Nanjing
Abstract :
A novel adaptive genetic algorithm (NAGA), which improves the global search ability and convergence of solutions by adjusting the crossover and mutation probability automatically, is presented for the design optimization of linear induction motors (LIM). Results by the proposed algorithm are compared with another algorithm to demonstrate the superiority and feasibility of the proposed NAGA.
Keywords :
genetic algorithms; linear induction motors; machine theory; adaptive genetic algorithm; global search ability; linear induction machines optimization; Algorithm design and analysis; Aluminum; Design optimization; Genetic algorithms; Genetic mutations; Induction machines; Induction motors; Optimization methods; Stochastic processes; Topology; Adaptive genetic algorithm; Linear induction machines; Uniform design; optimization;
Conference_Titel :
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3826-6
Electronic_ISBN :
978-7-5062-9221-4
