Abstract

Simulated annealing is a powerful method to numerically treat nonlinear optimization problems. The algorithm is advantageous in respect to flexibility and independence of start conditions. However, a drawback is its slow rate of convergence compared to projection procedures.

© 1991 Optical Society of America