From Wikipedia, the free encyclopedia.
Random optimization is the name applied to a class of algorithms which can be used to solve optimization problems.
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
