Search

Abstract We discuss the noisy optimisation problem, in which function evaluations are subject to random noise. Adaptation of pure random search to noisy optimisation by repeated sampling is considered. We introduce and exploit an improving bias condition on noise-affected pure random search algorithms. Two such algorithms are considered; we show that one requires infinite expected work to proceed, while the other is practical. [ABSTRACT FROM AUTHOR]

Abstract This discussion paper considers the use of stochastic algorithms for solving global optimisation problems in which function evaluations are subject to random noise. An idea is outlined for discussion at the forthcoming Stochastic Global Optimisation 2001 workshop in Hanmer in June; we propose that a noisy version of pure random search be studied. [ABSTRACT FROM AUTHOR]