Random optimization is relatively little known, but can be compared with genetic algorithms, and often random optimization outperforms other methods with significantly faster convergence.
References:
Baba, N (1989) A new approach for finding the global minimum of error functions of neural networks, Neural Networks, vol 2, pp 367-373
Matyas, J (1965), Random optimization, Automation and remote control, vol 26, pp 246-253
Solis, F.J and Wets, R.J (1981), Minimization by random search techniques, Mathematics of operations research, vol 6, no 1, pp 19-30