Ry. Tang et al., COMBINED STRATEGY OF IMPROVED SIMULATED ANNEALING AND GENETIC ALGORITHM FOR INVERSE PROBLEM, IEEE transactions on magnetics, 32(3), 1996, pp. 1326-1329
A combined strategy of an improved Simulated Annealing(SA) algorithm a
nd genetic algorithm is presented in this paper, with the goal of redu
cing the computational expenses. The improvements made on SA algorithm
include two parts, i.e., the adaptive regulating for the step vector,
and the dynamic testing for the equilibrium of Metropolis process. Th
e proposed strategy has both the advantage of SA algorithm, the abilit
y to avoid being trapped in a local optimum, and that of genetic algor
ithm, the ability to use the information about the searched states for
next iteration. A practical application on geometry optimization of p
ole shoes in large salient pole synchronous generators is effectively
implemented using the strategy. The numerical results show that the nu
mbers of iterations used by executing the combined strategy are only a
bout 75% of those by executing basic SA algorithm.